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Author SHA1 Message Date
Cameron Cordes
dbbd4470a5 auto-tag: Apollo tag client + probe binary
Adds ai::tag_client mirroring face_client for Apollo's RAM++ endpoint
(APOLLO_TAG_API_BASE_URL falling back to APOLLO_API_BASE_URL), and a
throwaway probe_auto_tags binary that walks image_exif and prints tags
without writing the DB. Lets us eyeball RAM++ output quality + threshold
before committing to a schema and per-tick drain.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-13 20:01:55 -04:00
22ce1a20e7 Merge pull request 'feature/library-patch-endpoint' (#94) from feature/library-patch-endpoint into master
Reviewed-on: #94
2026-05-13 13:44:36 +00:00
Cameron Cordes
7ec156fc05 libraries: accept newline as an excluded_dirs separator
Splits parse_excluded_dirs_column on `,`, `\n`, AND `\r` so a textarea
submit with one entry per line works the same as comma-separated.
Mixed input (`a, b\nc`) parses cleanly too — the frontend can paste
from any source without preprocessing.

Motivated by the "forgot the comma" footgun: typing
`.thumbnails .thumbnails2` in a single-line input today stores a
never-matching component pattern. With newlines as a first-class
separator and the frontend switching to a textarea, the natural
one-per-line UX makes that mistake impossible.

The DB store form stays comma-joined (normalize_excluded_dirs_input
hasn't changed) so existing rows are unaffected and no migration is
needed. Newline support matters mostly for the inbound write path;
mirroring it on the read side keeps the parser round-trip safe in
case anything writes a newline form directly.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-13 09:23:51 -04:00
Cameron Cordes
439532377d libraries: validate excluded_dirs entries on write
Reject the silent-footgun shapes that PathExcluder would store but
never match. The watcher would still walk past every photo as if the
exclude wasn't there, and the operator would have no signal that
their entry is dead. Caught at PATCH time with a descriptive 422.

Rules:
- Backslash anywhere → "use forward slashes" (catches \photos,
  photos\2024, \\server\share — Windows-typed entries land in the
  component-pattern bucket and never fire).
- Drive-letter prefix (Z:, Z:/...) → "relative to library root" —
  excludes are root-relative, not absolute system paths.
- Multi-segment name with no leading slash (photos/2024) →
  "did you mean /photos/2024?" — the common "I forgot the slash"
  typo, today silently stored as a component pattern that never hits.
- `..` segments in a path entry → "doesn't normalise". base.join()
  doesn't canonicalise, so the resulting prefix never matches.
- Bare "/" → "almost certainly a typo" for the library root.

Trailing slashes on path entries are stripped silently. Eight new
tests cover each rejection plus the trailing-slash normalisation
and the all-or-nothing failure mode of normalize_excluded_dirs_input
(one bad entry aborts the whole patch rather than silently applying
N-1 of N changes).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-13 09:02:29 -04:00
Cameron Cordes
ce9fa94cb4 libraries: surface globals, normalise excluded_dirs on write
Two follow-ups to the PATCH endpoint:

1. GET /libraries now returns ``global_excluded_dirs`` alongside the
   library list — the union-with-globals semantics is invisible from
   the per-library row alone, and the admin UI needs to show what's
   already being skipped before the operator adds entries that would
   duplicate.

2. PATCH /libraries/{id} canonicalises the excluded_dirs string on
   write via the new ``normalize_excluded_dirs_input``: trims per
   entry, drops empties, dedupes preserving first-occurrence order,
   comma-joins without inner whitespace. Empty / whitespace-only →
   NULL. Round-trip stable so re-saving an entry produces an
   identical row.

Five new tests cover the empty / whitespace, trim, dedup, round-trip,
and overlap-with-globals cases. effective_excluded_dirs continues to
keep overlapping entries between globals and per-library on purpose —
PathExcluder accepts repeats and there's no behavioural reason to
dedupe at merge time.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-13 08:58:04 -04:00
Cameron Cordes
b3124437ec libraries: PATCH /libraries/{id} with live-apply
Adds an HTTP mutation surface for `libraries.enabled` and
`libraries.excluded_dirs`, replacing the SQL-only workflow noted in
CLAUDE.md. Apollo's Settings panel calls this from the LIBRARIES
section so the operator no longer has to ssh + sqlite3 to flip a
library off or edit its excludes.

Live-apply (no restart) via a new `live_libraries: Arc<RwLock<Vec<
Library>>>` field on AppState. The existing immutable `libraries`
Vec stays for hot-path handlers that only need stable id → root_path
lookups, avoiding a 19-call-site refactor. The watcher and
cleanup_orphaned_playlists now take the lock instead of a Vec
snapshot and re-read at the top of each tick, so `enabled` /
`excluded_dirs` changes are picked up within one
WATCH_QUICK_INTERVAL_SECONDS. The GET /libraries handler also reads
through the live view.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-13 08:47:35 -04:00
74bf693878 Merge pull request 'feature/date-backfill-null-only' (#93) from feature/date-backfill-null-only into master
Reviewed-on: #93
2026-05-12 18:42:21 +00:00
Cameron Cordes
2d56047497 Drop fs_time from date-backfill eligibility
The drain queried `date_taken IS NULL OR date_taken_source = 'fs_time'`
ORDER BY id ASC LIMIT 500 every watcher tick. The resolver is
deterministic on file bytes + filename + fs metadata, so any row that
landed on fs_time once landed there again on every retry — the drain
spun on the same lowest-id rows in perpetuity, never advancing to
rows 501+ while still logging more_remain=true.

Side effect: 500 auto-commit UPDATEs per tick sustained the SQLite
write lock long enough that other writers on separate DAO connections
hit the 5s busy_timeout. Manifested as intermittent 500s on
PATCH /image/faces/{id} that succeeded on retry.

Narrow the partial index and query predicate to `date_taken IS NULL`.
If exiftool installs or a new filename regex lands, an operator can
re-resolve fs_time rows out-of-band rather than re-introducing the
steady-state churn.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-12 14:37:36 -04:00
Cameron Cordes
3427c2916c Log 500-return paths in PATCH /image/faces/{id}
The four 500-return paths in update_face_handler returned e.to_string()
in the body but never logged. When a face PATCH failed with a 16-byte
body and no log entry, the cause (SQLITE_BUSY from cross-DAO writer
contention exhausting the 5s busy_timeout) was invisible. Surface the
full anyhow chain via {:#} on each path so the diesel cause is in the
log even when the response body only shows the top-level context.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-12 14:37:26 -04:00
6a3e37b7dc Merge pull request 'feature/split-main-rs' (#92) from feature/split-main-rs into master
Reviewed-on: #92
2026-05-12 17:02:06 +00:00
Cameron Cordes
9f8a69fc6d Split main.rs: extract watcher loop into src/watcher.rs
main.rs drops from 1200 → 346 lines (90% smaller than the pre-branch
3542). What's left is the startup wiring it was always meant to be:
.env, migrations, AppState construction, route registration, server
bind. The four background-loop functions move into src/watcher.rs:

- watch_files (310 lines) — quick/full scan tick, per-library probe,
  backfill drain dispatch, missing-file scan, back-ref refresh,
  orphan GC.
- process_new_files (351 lines) — file walk → EXIF write →
  face-candidate build → HLS / preview-clip queueing →
  reconciliation. The "biggest untested chunk" from the earlier
  audit.
- cleanup_orphaned_playlists (167 lines) — separate slower-tick
  thread.
- playlist_needs_generation — small mtime-comparison helper.

Plus 4 unit tests for playlist_needs_generation (covers missing
playlist, newer playlist, newer video, video-missing-metadata
fallback).

main.rs's imports correspondingly shrink — Addr, HashSet, WalkDir,
Utc, InsertImageExif, and the bulk of video::actors all leave with
the watcher. CLAUDE.md updated to reflect the new module layout
(layered architecture box + module map for the face-detection
section).

cargo test --bin image-api: 329 passing (no regression).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-12 12:54:37 -04:00
Cameron Cordes
bdb69c7d37 Split main.rs: extract HTTP handlers into src/handlers/
main.rs drops from 2935 → 1200 lines, freed for startup wiring +
the watcher. The 16 route handlers move into three domain-grouped
files under src/handlers/:

- handlers/favorites.rs (128 lines): favorites, put_add_favorite,
  delete_favorite.

- handlers/video.rs (665 lines): generate_video, stream_video,
  get_video_part, get_video_preview, get_preview_status. The 5
  pre-existing get_preview_status integration tests move with the
  handler (still pass against TestPreviewDao + AppState::test_state).

- handlers/image.rs (1003 lines): get_image (with the
  hash/library-scoped/bare-legacy thumb lookup), upload_image,
  get_file_metadata, set_image_gps, get_full_exif, set_image_date,
  clear_image_date. Helpers (create_circular_thumbnail,
  build_metadata_response_for_date_mutation) and request structs
  (SetGpsRequest, SetDateRequest, ClearDateRequest, UploadQuery)
  travel with them.

main.rs's import block shrinks from ~50 lines to ~22 as everything
HTTP-specific (NamedFile, mp::Multipart, BytesMut, Span, KeyValue,
StreamExt, …) moves with the handlers. The is_video_file wrapper
also goes — remaining callers in watch_files / cleanup use
file_types::is_video_file directly.

cargo test --bin image-api: 325 passing (no regression).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-12 12:38:17 -04:00
Cameron Cordes
bec9857426 Split main.rs: extract backfill drains and thumbnails into modules
main.rs drops from 3542 → ~2930 lines by moving:

- src/backfill.rs (new): backfill_unhashed_backlog,
  backfill_missing_date_taken, backfill_missing_content_hashes,
  build_face_candidates, process_face_backlog. Now unit-tested for
  the first time — 5 tests covering cap behavior, library-id
  filtering, missing-on-disk skip, and the video/unhashed/scanned
  filters on face-candidate selection.

- src/thumbnails.rs (new): unsupported_thumbnail_sentinel,
  generate_image_thumbnail, create_thumbnails, update_media_counts,
  is_image, is_video, plus the IMAGE_GAUGE / VIDEO_GAUGE Prometheus
  metrics. Replaces the no-op stubs that used to live in lib.rs.
  4 new unit tests for the sentinel path math and the
  walker-counts-images-vs-videos smoke path.

Supporting:
- SqliteExifDao::from_shared (test-only) so an SqliteExifDao and
  SqliteFaceDao can share one in-memory connection — required to
  test build_face_candidates against the real join.
- files.rs / video/{mod,actors}.rs import from crate::thumbnails::*
  instead of the now-removed stubs in lib.rs.

cargo test --bin image-api: 325 passing (was 314).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-12 12:22:02 -04:00
05ec5d0c70 Merge pull request 'feature/knowledge-curation' (#91) from feature/knowledge-curation into master
Reviewed-on: #91
2026-05-12 15:40:55 +00:00
Cameron Cordes
e67e00ef8a knowledge: predicate-quality nudge + bulk-reject endpoint
Two coupled changes to fight the speech-act-predicate problem
(facts like (Cameron, expressed, "I'm tempted to...")):

1. System prompt grows an explicit predicate-quality rule. The
   agent is told to use relationship-shaped verbs (lives_in,
   works_at, attended, is_friend_of, interested_in), and is
   given an explicit DON'T list (expressed, said, mentioned,
   stated, quoted, noted, discussed, thought, wondered). Plus a
   concrete Bad / Good example contrasting the noise pattern
   with the structured paraphrase the agent should be writing.
   Stops the bleed for new insights.

2. Cleanup tools for the legacy noise that's already in the
   table:
   - get_predicate_stats(persona, limit) returns
     [(predicate, count)] sorted desc — feeds the curation UI's
     PREDICATES tab.
   - bulk_reject_facts_by_predicate(persona, predicate, audit)
     flips every ACTIVE fact under that predicate to 'rejected'
     in one transaction, stamping last_modified_* so the action
     is attributable + reversible per-fact through the entity
     detail panel. REVIEWED facts under the same predicate are
     left alone — the curator may have hand-approved an
     exception ("interested_in" might be largely noise but a
     reviewed entry is intentional).

New HTTP endpoints:
   GET  /knowledge/predicate-stats?limit=
   POST /knowledge/predicates/{predicate}/bulk-reject

Persona-scoped via the existing X-Persona-Id header.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 21:50:26 -04:00
Cameron Cordes
fb078b4906 knowledge: normalize legacy entity_type values
One-shot migration that re-applies the synonym map from
`normalize_entity_type` over every existing row, so legacy
entries written before that helper landed in upsert_entity stop
needing client-side workarounds.

  person ← person | people | human | individual | contact
  place  ← place | location | venue | site | area | landmark
  event  ← event | occasion | activity | celebration
  thing  ← thing | object | item | product

Unknown types ("friend", "family", etc.) get a lowercase+trim
sweep so at minimum case variants collapse — the curator can
merge or rename them via the curation UI from there.

`UPDATE OR IGNORE` skips rows that would violate UNIQUE(name,
entity_type) after the rewrite (e.g. an existing ("Sarah",
"person") + ("Sarah", "Person") pair). The duplicate survives
unchanged so it can be merged through the normal curation flow
rather than silently disappearing.

Idempotent: every UPDATE is conditional on `entity_type !=
canonical`, so re-running the migration is a no-op. The down
migration is intentionally inert — we don't have per-row
history of the original strings and the rewritten values stay
semantically correct.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 21:42:51 -04:00
Cameron Cordes
d123cde333 knowledge: entity-graph endpoint for force-directed view
New GET /knowledge/graph?type=&limit= returns the data the
curation UI's graph tab needs:
  - nodes = entities with at least one in-scope fact (rejected /
    superseded excluded). Carries fact_count for visual sizing.
    Top-N by count desc; default cap 200 (clamped 1..1000).
  - edges = relational facts (object_entity_id set) grouped by
    (subject, object, predicate) so 3 "is_friend_of" facts
    between the same pair collapse into one edge with count=3.

Two raw SQL queries: an INNER JOIN onto a persona-scoped fact-
count subquery for nodes (skips 0-fact entities entirely so the
sim doesn't waste time on disconnected islands), then a follow-
up GROUP BY over the persona-scoped fact set restricted to the
node id set via IN clauses (ids are i32 so inlining is safe).

Pairs with the Apollo-side GraphPanel that runs d3-force over
the returned payload and renders SVG with click-to-open.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 21:26:02 -04:00
Cameron Cordes
6dca0c027d fmt: cargo fmt sweep
No logic changes - line reflow, brace placement, and method-chain splits
across handlers / personas / state / faces / knowledge / insights_dao /
knowledge_dao / populate_knowledge. Picked up incidentally while running
fmt for the sms-search work.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 19:21:00 -04:00
Cameron Cordes
7329cc5ce7 insights: push sms search filters server-side, render snippets, expand fts5 docs
- Refactor search_messages_with_contact -> search_messages(query, &SmsSearchParams)
  exposing date_from / date_to / offset / is_mms / has_media; drop the over-fetch
  + client-side date post-filter that could silently drop in-window hits past
  position 100.
- Surface SMS-API's <mark>-wrapped snippet for MMS messages that only matched
  via message_parts_fts (attachment text / filename) - pre-snippet, those
  rendered as a blank body preview to the LLM.
- Expose is_mms / has_media on the search_messages tool schema; expand the
  FTS5 syntax docs with worked examples for phrase / prefix / boolean / NEAR
  / grouping so the model picks the right operator.
- Unit tests for format_search_hits (body fallback, snippet preferred, MMS
  attachment-only regression, empty-snippet fallback) and strip_mark_tags.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 19:20:19 -04:00
Cameron Cordes
6620fa48d7 knowledge: consolidation proposals endpoint
Finds near-duplicate entities the upsert-time cosine guard didn't
catch — typically legacy data from before that guard landed, or
pairs whose embeddings sit between 0.85 (default proposal floor)
and 0.92 (auto-collapse threshold). Pure read-side feature; the
actual merging still goes through the existing
/knowledge/entities/merge action.

New DAO method `find_consolidation_proposals(threshold,
max_groups)`:
  - Loads every non-rejected entity with an embedding.
  - Partitions by entity_type so a person can't cluster with a
    place.
  - Pairwise cosine, edges above threshold feed a union-find for
    transitive grouping (Sara → Sarah → Sarah J. all land in one
    cluster).
  - Tracks min/max cosine per component so the UI can show "how
    tight" each cluster is before clicking in.
  - Returns groups of >= 2 sorted by size desc then max cosine
    desc; trimmed to `max_groups`.

New endpoint `GET /knowledge/consolidation-proposals?threshold=
&limit=` accepts the threshold (clamped 0.5–0.99 to prevent the
"every entity in one mega-cluster" case) and returns groups with
per-entity persona fact-count breakdowns baked in — saves the UI
a separate query per cluster member.

ConsolidationGroup is exported through database/mod.rs so the
handler can use it without depending on knowledge_dao internals.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 18:43:11 -04:00
Cameron Cordes
89d0a6527c knowledge: per-entity persona breakdown for list + detail
Entities are global; facts are persona-scoped. Under the active
persona an entity can read as "0 facts" while having plenty under
other personas the user owns — the curation UI had no way to
surface that gap. Adds a batched DAO method
`get_persona_breakdowns_for_entities` that returns
{entity_id → [(persona_id, count)]} in one query (group by
subject + persona, user-scoped, status != rejected), and wires it
into both /knowledge/entities list rows and
GET /knowledge/entities/{id}.

EntitySummary grows an optional `persona_breakdown` field
(skipped on serialization when None — keeps PATCH responses
unchanged). EntityDetailResponse carries the breakdown as a
non-optional Vec since the detail endpoint always populates it.

One extra query per list page (50 entities → 50 subject ids
batched in one IN clause); single-entity GET adds one round trip.
Indexed by (subject_entity_id, persona_id) implicitly via the
existing user-persona indexes on entity_facts.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 18:29:20 -04:00
Cameron Cordes
f200466508 knowledge: forbid markdown in synthesized merge descriptions
System prompt now explicitly enumerates the markdown forms the
model shouldn't emit (bold, italics, headings, bullets, lists,
code fences) on top of the existing "no preamble, no quotes"
constraints. Some local models default to markdown-shaped
output for descriptions and the curation UI is plain-text,
which would render the asterisks and hashes literally.

The output cleaning step picks up a parallel sweep: strip code
fences, leading bullets / headings, wrapping quotes, and naive
inline emphasis markers (** and __). Rare enough that the
plain-replace is fine; not trying to parse markdown.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 16:49:02 -04:00
Cameron Cordes
afac02cade knowledge: synthesize-merge endpoint for LLM-curated descriptions
New POST /knowledge/entities/synthesize-merge { source_id,
target_id } that calls the local Ollama with both entities' names
+ descriptions and returns a synthesized merged-description draft.
Read-only on the database — the curation UI uses the response as
the editable seed in the merge picker; the actual merge still
requires a follow-up PATCH-target-description + POST /merge.

The handler drops the KnowledgeDao lock before the LLM call so
other knowledge reads aren't blocked while generation runs
(typically seconds). Failure mode is 503 with an explicit hint
that the UI should fall back to skip-synthesis — keeps the merge
action working when the model is offline.

Output is lightly cleaned (leading "Merged description:" /
surrounding quotes stripped) since small models reach for those
patterns even with explicit "no preamble" guidance. Heavier
parsing isn't worth it — the curator edits anyway.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 16:37:26 -04:00
Cameron Cordes
fd4dd89bbb knowledge: agent self-correction with audit + per-persona gate + revert
Bundles three coupled changes so agent-side mutations stay
auditable and reversible:

1. Audit columns on entity_facts —
   `last_modified_by_model` / `last_modified_by_backend` /
   `last_modified_at`. Stamped on every mutation path
   (update_fact, supersede_fact, manual PATCH, manual supersede,
   the new revert). NULL on rows never touched since creation.
   Partial index on `last_modified_at WHERE NOT NULL` keeps the
   "show me recent edits" feed fast without bloating from legacy
   rows.

2. Per-persona gate `personas.allow_agent_corrections` (BOOLEAN,
   default 0). Defense in depth at two layers:
   - build_tool_definitions: when off, `update_fact` and
     `supersede_fact` aren't in the catalog at all, so even a
     hallucinated tool call by the model fails fast.
   - tool_update_fact / tool_supersede_fact: re-checks the persona
     flag at call time and returns an explicit "corrections
     disabled" error if it's somehow off (e.g. flag flipped mid-
     loop).
   ToolGateOpts grows the flag; current_gate_opts splits into
   `current_gate_opts` (no persona context, defaults closed) +
   `current_gate_opts_for_persona` for chat callers that have a
   persona id. Both call sites in insight_chat are updated.

3. Revert action — new DAO method `revert_supersession` +
   `POST /knowledge/facts/{id}/restore`. Flips status back to
   'active', clears `superseded_by`, clears `valid_until` (we
   don't track whether it was hand-set vs auto-stamped, so the
   safe reset is to drop it — user can re-bound after). Stamps
   `last_modified_*` so the revert itself is attributable.

Manual paths (PATCH / supersede via HTTP, plus restore) stamp the
audit columns with `("manual", "manual")`. Agent paths stamp the
loop-time chat model and backend (mirroring the existing
created_by_* convention).

FactDetail in the HTTP response now carries the audit triple
alongside the existing provenance. Apollo wires the new field set
in the matching commit.

PersonaView / UpdatePersonaRequest grow `allowAgentCorrections`;
the PersonaPatch + InsertPersona + bulk_import paths thread it.

317 lib tests pass, including unchanged update_fact / supersede
DAO tests (now passing audit=None — None means "no provenance
context to attribute", legacy semantics).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 20:56:56 -04:00
Cameron Cordes
86c331571d knowledge: per-persona reviewed-only mode + agent reads include reviewed
Two coupled changes to the agent's recall surface:

1. Default scope expanded. recall_facts_for_photo and recall_entities
   used to filter to status='active' only — which silently dropped
   'reviewed' (human-verified) facts. Now they surface active +
   reviewed by default. Reviewed is strictly more trusted than
   active and shouldn't have been hidden. Rejected and superseded
   stay filtered.

2. New persona toggle `reviewed_only_facts` (BOOLEAN, default false,
   migration 2026-05-10-000400). When set, the agent's recall on
   that persona returns ONLY facts with status='reviewed' — strict
   mode for tasks where hallucinated agent claims are particularly
   costly. Wired:
   - schema.rs / Persona / InsertPersona / PersonaPatch grow the
     field.
   - PersonaView returns it as `reviewedOnlyFacts` (camelCase wire).
   - PUT /personas/{id} accepts it (mobile editor surfaces it).
   - InsightGenerator now carries a PersonaDao reference so
     recall_facts_for_photo can read the active persona's flag at
     start; one extra read per recall, cheap.

Composes with include_all_memories: that operates on the persona
*scope* axis (single vs hive), reviewed_only_facts on the *status*
axis. They're orthogonal.

Legacy persona rows pick up the default false on migration; no
behavior change unless explicitly toggled. The 4 existing persona
construction sites (one production, two tests, one InsertPersona in
knowledge_dao tests) all default the field. populate_knowledge bin
+ state.rs constructors also wire the new persona_dao arg.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 20:21:39 -04:00
Cameron Cordes
f53338923d knowledge: stamp model + backend on facts for audit
Adds two nullable TEXT columns to entity_facts —
`created_by_model` (LLM identifier) and `created_by_backend`
("local" / "hybrid" / "manual" / NULL) — so the curator can audit
which configurations produce good fact-keeping and which produce
noise.

photo_insights already carries model_version + backend, and
entity_facts.source_insight_id links to it, but:
  - source_insight_id is set post-loop, so chat-continuation and
    regenerated-insight facts lose the link.
  - JOINing per read is more friction than embedding provenance on
    the row itself.
  - Manual facts (POST /knowledge/facts) have no insight at all and
    need their own "manual" provenance marker.

Threading: execute_tool grows `model` + `backend` params, passed
from the three call sites (agentic insight loop, chat single-turn,
chat stream) using the loop-time `chat_backend.primary_model()` +
`effective_backend` already in scope. tool_store_fact stamps the
new fact accordingly; manual create_fact stamps backend="manual".
Legacy rows leave both NULL — pre-tracking data can't be back-
filled reliably from training_messages without burning compute.

Indexes are partial (WHERE NOT NULL) so legacy rows don't bloat
them, and "show me all facts from model X" stays fast.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 20:05:14 -04:00
Cameron Cordes
85f3716379 knowledge: fact supersession + photo-date valid_from
Two Phase-2 followups in one commit since they're coupled at the
write path:

* Agent populates valid_from from the source photo's date_taken
  when calling store_fact. Loose semantics — date_taken is *evidence
  at that date*, not strictly when the fact started being true — but
  gives the curator a calendar anchor and pairs with supersession to
  close intervals cleanly. valid_until stays NULL (a single photo
  can't tell us when something stopped). Honours the existing
  upsert_fact dedup (corroborated facts keep their first-recorded
  valid_from).

* Supersession: new column entity_facts.superseded_by INTEGER
  (migration 2026-05-10-000200), new status value 'superseded',
  new DAO method supersede_fact, new HTTP endpoint
  POST /knowledge/facts/{id}/supersede.

  Marking an old fact as replaced by a new one atomically: flips
  status to 'superseded', sets superseded_by, and stamps
  valid_until from the new fact's valid_from (when not already
  set). delete_fact clears dangling supersession pointers in the
  same transaction so the column never points at a missing row —
  no FK because SQLite can't ALTER ADD with REFERENCES, but the
  DAO maintains the invariant.

Pairs with conflict detection from the previous slice: once the
old fact's valid_until is closed, its interval no longer overlaps
the new fact's, so they stop flagging — the supersede action
resolves the conflict.

Two tests pin the contract: supersede stamps valid_until from
new.valid_from while respecting an existing valid_until, and
deleting the supersedeR clears the dangling pointer while leaving
the old fact's 'superseded' status in place for history.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 19:47:06 -04:00
Cameron Cordes
01f5ad7527 knowledge: valid-time on facts + interval-aware conflict detection
Adds bitemporal support to entity_facts. Existing `created_at` is
transaction time (when we recorded the fact); the new
`valid_from` / `valid_until` BIGINT columns are valid time (when the
fact is/was true in the real world). NULL on either side = unbounded
on that side, both NULL = "always-true / unknown" — matches the
default state of every legacy row, no backfill needed.

The split matters for time-bounded predicates like
is_in_relationship_with / lives_in / works_at: recording the fact
once doesn't mean the relationship is still ongoing. Same predicate
across different windows ("lives_in NYC 2018-2020", "lives_in SF
2020-present") is no longer a conflict — the interval-aware check
in get_entity only flags pairs whose windows overlap. Facts with no
valid-time data still flag against everything (worst case for legacy
rows — user adds dates to suppress).

API surface:
- POST /knowledge/facts accepts optional valid_from / valid_until.
- PATCH /knowledge/facts/{id} accepts both with tri-state semantics:
  field omitted = leave alone, JSON null = clear to NULL, number =
  set. Implemented via a small serde helper around Option<Option>.
- GET /knowledge/entities/{id} surfaces both fields per fact and
  uses them in conflict detection.

Agent path (insight_generator) writes NULL/NULL for now — deriving
valid_from from the source photo's date_taken is slated for a
follow-up agent tool alongside Phase 2's supersession.

Test pins set + clear semantics via update_fact: setting both
bounds, leaving them alone on a subsequent patch, then clearing
valid_until back to NULL.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 19:25:55 -04:00
Cameron Cordes
bcd5312953 knowledge: detect same-predicate object conflicts at read time
GET /knowledge/entities/{id} now flags facts as `in_conflict` when
another active fact shares the same predicate but disagrees on the
object (entity id or text value). Pure read-time computation in the
handler — group facts by predicate, distinct-object count > 1 flags
all members. No schema change; same shape as `is_current` on photo
insights.

The flag is intentionally a *signal*, not a hard constraint. Some
predicates are legitimately multi-valued (friend_of, tagged_in,
appears_in) — the curator UI surfaces the amber accent and lets the
user reject the stale fact, accept both, or supersede one later
once the supersession column lands.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 19:14:58 -04:00
Cameron Cordes
0b8478a5e4 knowledge: list sort + persona-scoped fact_count per entity
Two related additions to /knowledge/entities:

- New EntitySort enum (UpdatedDesc default, NameAsc, FactCountDesc)
  surfaced via `?sort=updated|name|count`. NameAsc clusters near-
  duplicate names so dupes stand out at a glance; FactCountDesc
  surfaces heavily-used entities and demotes 0-fact noise to the
  bottom.

- New `list_entities_with_fact_counts` DAO method that returns each
  entity alongside a persona-scoped count of its non-rejected facts
  (subject side). Persona scope follows X-Persona-Id via the
  existing resolve_persona_filter chain — Single filters on
  (user_id, persona_id), All unions across the user's personas.
  Implemented as one raw SQL query with a LEFT JOIN to a fact-count
  subquery and ORDER BY tied to the chosen sort, so count-sort needs
  no second round trip.

The agent's existing list_entities call site is unchanged — it
doesn't need persona-scoped counts and the trait method stays cheap.
EntitySummary grows an Option<i64> fact_count (skip_serializing_if
none) so PATCH responses stay shaped as before.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 16:04:13 -04:00
Cameron Cordes
0e2b18224f knowledge: pre-delete relational facts so entity delete succeeds
DELETE /knowledge/entities/{id} was 500ing on any entity that was the
object of a relational fact. entity_facts.object_entity_id has
ON DELETE SET NULL, but the table also has
CHECK (object_entity_id IS NOT NULL OR object_value IS NOT NULL) —
purely relational facts (subject + predicate + object_entity_id, no
object_value, like "Alice is_friend_of Bob") would have both NULL
after SET NULL fired, the CHECK would abort, and the whole DELETE
would fail with a CHECK violation. The user just saw QueryError
because the DAO swallowed the diesel error string.

Wrap delete_entity in a transaction that first deletes facts where
the entity is the object AND object_value is null, then deletes the
entity. Surviving siblings (typed facts about the entity as subject)
are CASCADE'd by the FK as before. Also start surfacing the actual
diesel error in a warn log before collapsing to DbErrorKind so future
similar issues don't masquerade as the opaque QueryError.

A schema-level fix (changing object FK to ON DELETE CASCADE via a
table-rebuild migration) is the cleaner long-term resolution and is
slated for Phase 2; the DAO-side pre-delete is sufficient and less
invasive in the meantime.

Test pins the contract: a relational fact pointing at the deleted
entity is removed, an unrelated typed fact about an unrelated entity
survives, and the entity itself is deleted.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 15:44:38 -04:00
Cameron Cordes
f7ce3d2b22 knowledge: include library_id in photo_links response
The PhotoLinkDetail in /knowledge/entities/{id} was dropping the
library_id field, leaving consumers no way to construct a
content-routed thumbnail URL. Apollo's curation screen was falling
through to library=0 (the FastAPI default) and getting 400s.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 15:19:37 -04:00
Cameron Cordes
d7aee4f228 knowledge: cosine dedup, fact create endpoint, recall nudge
Phase 1 of the knowledge curation work. Three small server-side changes
to support an Apollo-side curation surface and reduce the agent's near-
duplicate output rate going forward:

- upsert_entity grows an embedding-cosine fallback after the exact name
  match misses. New entities whose embedding sits above
  ENTITY_DEDUP_COSINE_THRESHOLD (default 0.92) against any same-type
  active entity collapse onto the existing row. Eliminates the Sarah /
  Sara / Sarah J. trio the FTS5 prefix check was missing.
- POST /knowledge/facts symmetric with the existing PATCH/DELETE so the
  curation UI can create facts directly. Persona-scoped via X-Persona-Id;
  validates subject (and optional object) entity existence; reuses
  KnowledgeDao::upsert_fact so corroboration semantics match the agent
  path.
- One sentence in build_system_content telling the agent to call
  recall_entities before store_entity when a name resembles something
  already known. Cheap; complements the DAO-layer guard.

Includes upsert_entity_collapses_near_duplicate_by_embedding test
covering both the collapse-on-near-match path and the don't-collapse-on-
unrelated-embedding path.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 15:16:05 -04:00
827a78dd79 Merge pull request 'feature/persona-fk-and-guard' (#90) from feature/persona-fk-and-guard into master
Reviewed-on: #90
2026-05-10 18:42:27 +00:00
Cameron Cordes
08a5f46be1 chat: scope insight lookup by library_id to fix regen-shadow bug
When a photo exists in more than one library and the user
regenerates its insight from library A's chat, the regenerate
streams cleanly, store_insight flips library A's old row to
is_current=false, and inserts a new is_current=true row tagged
(library A, rel_path). On the next history fetch the user sees
their old transcript — the regenerate appears to vanish.

The cause: get_insight(file_path) filters on rel_path + is_current
only, so library B's untouched is_current=true row for the same
rel_path satisfies the query and gets returned by SQLite's .first()
ahead of A's new row. Because get_insight is also what
chat_turn_stream uses to decide bootstrap vs. continuation, the
next chat turn after the shadow hit also routes against the
wrong insight, so update_training_messages corrupts library B's
transcript with library A's chat.

Fix: add get_current_insight_for_library(library_id, file_path)
filtered on (library_id, rel_path, is_current=true) and route the
chat surface (load_history, chat_turn{,_stream}, rewind_history)
through it. load_history falls back to the cross-library
get_insight when the scoped lookup misses — preserves the
"scalar data merges across libraries" intent for the case where
the active library has no insight but another does. The path-only
get_insight stays for callers that don't have library context
(populate_knowledge, the photo-grid metadata fetch).

chat_history_handler stops dropping the parsed library on the
floor and threads it through. Single-library deploys see no
behaviour change.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 14:03:41 -04:00
Cameron Cordes
b9d9ba0320 chat: route search_messages({date}) to get_sms_messages
When the LLM calls search_messages with { date, limit } and no
query, it's making the predictable mistake of conflating the two
"messages"-shaped tools. The previous behaviour returned an error
that pointed it at get_sms_messages — correct, but burning a turn
on the misroute. Long photo-chat threads where the user asks
"what was happening that weekend?" hit this on small models
roughly half the time.

Now the date-string-without-query case transparently dispatches
to get_sms_messages with the same args (date / limit / days_radius
/ contact name all pass through unchanged) and prepends a short
"(Note: routed to get_sms_messages — prefer it directly next time)"
to the result. The model sees real data on its first try while
still learning the right tool for next time. Cases that don't have
a get_sms_messages equivalent (numeric contact_id, or start_ts /
end_ts windows) keep the original error so the model knows to
either supply a query or restructure its call.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 13:48:13 -04:00
Cameron Cordes
fbd769e475 personas: composite FK + built-in update guard
Two persona-infrastructure correctness fixes that go together because
the second one (FK with CASCADE) requires the first (preventing the
persona row from being mutated out from under its facts).

1. update_persona handler refuses name/systemPrompt edits to built-ins
   (409). includeAllMemories stays editable — that's a per-user
   preference, not the persona's identity. Mirrors the existing
   delete_persona guard. The DAO is intentionally permissive so the
   guard sits at the HTTP layer; persona_dao test pins that contract.

2. Migration 2026-05-10 adds user_id to entity_facts and a composite
   FK (user_id, persona_id) -> personas(user_id, persona_id) ON DELETE
   CASCADE. This closes two issues at once:

   - Persona orphans: deleting a custom persona used to leave its
     facts dangling forever, readable only via PersonaFilter::All.
     CASCADE now wipes them with the persona row.

   - Multi-user fact leakage: PersonaFilter::Single("default") used
     to surface every user's default-scoped facts. PersonaFilter is
     now { user_id, persona_id } and all read paths
     (get_facts_for_entity, list_facts, get_recent_activity) filter
     on user_id first. upsert_fact's dedup key extends to user_id so
     identical claims under shared persona names from different
     users no longer corroborate-bump each other's confidence.

   - user_id threads from Claims.sub.parse::<i32>().unwrap_or(1) at
     the chat / insight handlers through ChatTurnRequest, the
     streaming agentic loop, execute_tool, and into the leaf tools
     (tool_store_fact, tool_recall_facts_for_photo). The ".unwrap_or(1)"
     accommodates Apollo's service token whose sub is non-numeric on
     legacy mints.

   - Backfill picks the smallest user_id matching each legacy fact's
     persona_id so the FK holds for already-stored rows.

Five new knowledge_dao tests with FK-on connection: persona scoping
isolation, All-variant union per-user, dedup not crossing users,
CASCADE delete, FK rejection of unknown personas. Plus
dao_update_does_not_block_built_ins documenting where the
HTTP-layer guard lives.

Apollo coordinates separately — the matching changes there add the
/api/personas proxy and start sending persona_id on photo-chat turns.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 13:30:35 -04:00
79a1168724 Merge pull request 'faces: add person_id filter to /faces/embeddings; remove tag-bootstrap' (#89) from feature/faces-tab into master
Reviewed-on: #89
2026-05-10 15:49:18 +00:00
Cameron Cordes
a079065ae9 faces: add person_id filter to /faces/embeddings; remove tag-bootstrap
Pairs with the Apollo FACES-tab change. The new
POST /api/persons/{id}/similar-unassigned route on Apollo needs to
fetch one person's embeddings cheaply to compute the centroid;
adding a person_id query param to /faces/embeddings keeps that to a
single round-trip instead of paging the whole detected set
client-side. When both person_id and unassigned=true are supplied,
person_id wins (the explicit filter is the more specific intent).

Tag-bootstrap removal: bootstrap_candidates_handler,
bootstrap_persons_handler, /persons/bootstrap and
/tags/people-bootstrap-candidates route registrations, and the
heuristic helpers (is_plausible_name_token, looks_like_person) plus
their tests. Only Apollo called these; the migration is complete.
The persons.created_from_tag column stays - it's informational on
existing rows and removing it would be a destructive migration for
no benefit.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 11:30:37 -04:00
25233904aa Merge pull request 'personas: elevate to server with per-persona fact scoping' (#88) from feature/persona-knowledge-segmentation into master
Reviewed-on: #88
2026-05-10 03:44:26 +00:00
8c377324a1 Merge pull request 'video: handle unknown/short durations in thumb + preview gen' (#87) from fix/video-thumb-preview-edge-cases into master
Reviewed-on: #87
2026-05-10 03:12:58 +00:00
Cameron Cordes
5476ed8ac4 video: handle unknown/short durations in thumb + preview gen
`get_duration_seconds` now returns `Option<f64>` and falls back from
`format=duration` to `stream=duration`. Empty stdout no longer
parse-panics with "cannot parse float from empty string", which was
poisoning the preview-clip row with status=failed and re-queueing every
full scan (notably for GoPro LRV files). `generate_preview_clip` handles
the unknown-duration case by transcoding the whole file (capped at 10s).

`generate_video_thumbnail` seeks to ~50% of the probed duration instead
of a hardcoded `-ss 3`, with a first-frame fallback when the probe
returns nothing. Fixes the loop where short Snapchat clips (<3s) got
"missing thumbnail" logged on every scan because ffmpeg exited 0
without writing a frame, and never wrote the .unsupported sentinel
either.

Adds unit tests for `parse_ffprobe_duration` covering the empty-output,
N/A, multi-line, non-positive, and non-finite cases.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-09 23:08:16 -04:00
7350f1916a Merge pull request 'fix/manual-date-update' (#86) from fix/manual-date-update into master
Reviewed-on: #86
2026-05-10 02:53:20 +00:00
Cameron Cordes
9871c685b4 date-override: cargo fmt
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-09 21:23:11 -04:00
Cameron Cordes
108bbeb029 date-override: union semantics across libraries + slash forms
The date-override path used to look up `image_exif` strictly by
`(library_id, rel_path)` with only the forward-slash form, while
`/image/metadata`'s `get_exif` falls back across libraries and tries
both slash forms. A photo whose row sat under a different library_id
than its filesystem-resolved one — or whose rel_path was stored with
backslashes — rendered fine in the modal but 404'd on save.

`set_manual_date_taken` / `clear_manual_date_taken` now share a
`locate_image_exif_row` helper that mirrors `get_exif`'s union
semantics (scoped lookup first, library-agnostic fallback by rel_path
in both slash forms), then update by primary key so the write hits
exactly the row read. Inner anyhow errors are logged with
`(library_id, rel_path)` so the next failure mode is debuggable.

Handler-side: `resolve_library_param` errors no longer silently fall
back to the primary library (which would have masked the original bug
with a different "row not found"); a malformed library param now
returns 400. New `DbErrorKind::NotFound` lets the handler distinguish
genuine misses (404) from real DB failures (500).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-09 21:21:25 -04:00
Cameron Cordes
3e2f36a748 personas: elevate to server with per-persona fact scoping
Move personas off the mobile client into ImageApi as first-class
records, and scope entity_facts by persona so each one builds its own
voice over a shared entity graph. The new include_all_memories flag
lets a persona opt back into the full hive-mind pool for human
browsing of /knowledge/*; agentic generation always stays in-voice.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-09 17:59:20 -04:00
55a986c249 Merge pull request 'feature/streaming-insights' (#85) from feature/streaming-insights into master
Reviewed-on: #85
2026-05-09 20:57:16 +00:00
c52a646be2 Merge pull request 'memories: restore early-era Snapchat unix-epoch filenames' (#84) from feature/snapchat-early-era-dates into master
Reviewed-on: #84
2026-05-08 20:23:35 +00:00
Cameron Cordes
d32a7d7c3a memories: restore early-era Snapchat unix-epoch filenames
The recent blanket "snapchat-" prefix denylist (43f8f83) rejected ALL
Snapchat-prefixed filenames from timestamp parsing, which fixed the
sequential-ID false positives but also broke real unix-second
filenames from Snapchat's early era. `Snapchat-1383929602.jpg`
(2013-11-08 16:53:22 UTC) now falls through to fs_time — and on files
with broken filesystem metadata, fs_time pins to 1970.

Replace the blanket prefix denial with a tighter discriminator:
  - exactly 10 captured digits AND timestamp >= 2011-09-23 (Snapchat
    launch) → real unix epoch, accept
  - any other length under this prefix → sequential ID, reject

This keeps the existing rejections intact:
  Snapchat-1021849065.mp4          → 10 digits, 2002 < launch → reject
  Snapchat-1751031586660373917.jpg → 19 digits truncates to 16 → reject
And restores the regression case:
  Snapchat-1383929602.jpg          → 10 digits, 2013 ≥ launch → accept

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-08 16:22:57 -04:00
Cameron Cordes
3699e059a2 insight-chat: include Date taken + GPS in bootstrap photo context
The bootstrap system message gave the model a file path and (in
hybrid mode) a visual description, but no temporal anchor. Models
defaulted to today's date when calling get_sms_messages — Nov 2014
photos were getting "2024-03-11" passed as `date`, missing every
historical message and leading the model to confidently misreport
context.

This commit folds two more EXIF-sourced facts into the
--- PHOTO CONTEXT --- block:

  Date taken: <YYYY-MM-DD or "unknown">
  GPS: <lat, lon to 4dp>           (omitted when no GPS)

Resolution waterfall for date_taken matches the documented canonical
date pipeline at the EXIF / filename steps, but intentionally stops
short of the fs-time fallback `generate_agentic_insight_for_photo`
uses — for chat we'd rather show "unknown" than mislead the model
with an inode mtime. GPS is taken straight from EXIF when both
lat/lon are populated; absent GPS suppresses the line entirely so
the model doesn't hallucinate coordinates.

InsightGenerator gains a `fetch_exif(file_path)` accessor (crate-
visible) so the chat service doesn't need its own ExifDao plumbing.

build_bootstrap_system_message picks up two new params (date,
gps); existing tests updated and 5 new tests cover:
- date present / absent / waterfall (EXIF wins, filename fallback,
  None when neither source has it)
- GPS present / absent
- ordering (path → date → visual)

Total insight_chat unit tests: 33 (up from 27).
2026-05-08 11:14:39 -04:00
Cameron Cordes
a0ec1a5080 insight-chat: photo context belongs in system msg, not user turn
After refresh, the rendered transcript was showing two unwanted
artifacts in the initial user bubble:

  Photo file path: pics/DSC_5171.jpg
  please tell me about this photo and what was going on around it

  Please write your final answer now without calling any more tools.

Two distinct bugs:

1. Bootstrap was prepending `Photo file path: <path>` (and, in
   hybrid mode, the visual description block) into the user-turn
   content. The model needed it to call file_path-keyed tools, but
   the user could see it in their own bubble on replay.

2. The no-tools fallback ("Please write your final answer now…")
   was a synthetic user message we never stripped from history,
   so it persisted into training_messages, rendered as a second
   user bubble, AND wiped the prior tool-call accumulator inside
   load_history (user-turn handler clears pending_tools), which
   is why the tool invocations disappeared from the assistant
   bubble after refresh.

Fixes:

- New `build_bootstrap_system_message` helper composes the persona
  with a `--- PHOTO CONTEXT ---` block (path + optional visual
  description). Lives in the system message, not the user turn.
  The user's bubble shows only what they typed.
- Streaming agentic loop's no-tools fallback now records its
  insertion index and removes the synthetic user prompt from
  `messages` after the model responds. Final assistant content
  stays — it reads coherently on replay without the synthetic
  prompt above it. Applies to both bootstrap and continuation.

3 new tests cover the system-message composer (path-only, with
visual block, persona-trim). Total insight_chat unit tests: 27.
2026-05-08 11:07:03 -04:00
Cameron Cordes
24ecf2abd4 insight-chat: prepend Photo file path: <path> to bootstrap user turn
Bug: bootstrap user_content was just the user's typed message (plus
the hybrid visual description). Tools that take a file_path arg —
recall_facts_for_photo, get_file_tags, get_faces_in_photo — had no
way to learn the canonical path. Small models would invent
placeholders like "input_file_0.png" or call the tool with a name
guessed from a hidden multimodal input handle, neither of which
matched any real photo.

Fix: prepend a single-line "Photo file path: <normalized>\n\n" block
to user_content. Same shape generate_agentic_insight_for_photo
already uses for non-chat callers — kept the bootstrap minimal
(no date / GPS / tags pre-stuffing; the agentic loop can fetch
those via tools when needed).

Hybrid still injects the visual description block between the path
block and the user message; local mode just gets path + user text.
2026-05-08 10:59:35 -04:00
Cameron Cordes
a29ff406a1 insight-chat: extract bootstrap resolution helpers + unit-test them
resolve_bootstrap_system_prompt and resolve_bootstrap_backend run on
every bootstrap turn — they pick the persisted system prompt and the
chosen backend label. They were inline conditionals before; pulling
them out makes the rules testable without spinning up the full
streaming stack.

9 new tests cover:
- system prompt fallback to BOOTSTRAP_DEFAULT_SYSTEM_PROMPT for None,
  empty string, whitespace-only
- supplied non-empty prompts pass through verbatim, with interior
  newlines / spacing preserved (Apollo personas use multi-line tool
  listings)
- backend defaults to "local" for None / empty
- "local" / "hybrid" accepted case-insensitively with edge-trim
- unknown labels return a descriptive error

Total insight_chat tests: 24 (up from 15). No behaviour change.
2026-05-08 10:56:22 -04:00
Cameron Cordes
928efe49f9 insight-chat: bootstrap insight on first Discuss message + regenerate flag
Tap-Discuss-on-no-insight previously failed silently: ImageApi's
/insights/chat/stream required an existing agentic insight, errored
when missing, and emitted the failure as `event: error` — which the
frontend SSE consumer ignored (it listens for `error_message`).

This commit closes both gaps with a server-side state machine:

- /insights/chat/stream now branches on insight presence. Missing
  insight (or `regenerate: true` in the body) → bootstrap path:
  builds [System(req.system_prompt), User(req.user_message + image)],
  runs the agentic loop, generates a title, persists a new row via
  store_insight (which auto-flips priors). Existing insight →
  continuation path (unchanged behaviour).
- New `regenerate: bool` request field forces bootstrap even when an
  insight exists. Takes precedence over `amend`.
- `done` SSE payload field-name alignment with Apollo's frontend
  convention: prompt_eval_count → prompt_tokens, eval_count →
  eval_tokens, num_ctx echo added.
- `amended_insight_id` semantics broaden — now populated whenever the
  turn produced a new row (bootstrap, regenerate, or amend). Existing
  amend clients keep working unchanged; new clients get the new row's
  id for free.
- `event: error` → `event: error_message` so frontend errors stop
  silently dropping.

Refactor: extracted run_streaming_agentic_loop, build_chat_clients,
and generate_title as shared helpers between bootstrap and
continuation. Continuation path's outer logic moves to
run_continuation_streaming with no behaviour change.

Mobile-ready: any client (Apollo backend, mobile, future) sends one
request to /insights/chat/stream and gets the right path. Apollo's
proxy stays a dumb pipe.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-08 10:41:50 -04:00
bdafd39546 Merge pull request 'feature/insight-chat-improvements' (#83) from feature/insight-chat-improvements into master
Reviewed-on: #83
2026-05-07 22:19:12 +00:00
Cameron Cordes
8bd1a85070 insight-chat: cargo fmt sweep on the get_faces_in_photo additions
Single-line dao lock + reordered faces import. No logic changes.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 17:53:31 -04:00
Cameron Cordes
6f0c15d0c5 insight-chat: code-review polish on get_faces_in_photo
- Drop redundant `use anyhow::Context` inside has_any_faces (already
  imported at the module level).
- Drop dead `.unwrap_or("?")` on bound faces — the vec is filtered to
  is_some() so the fallback can never fire.
- Reorder the face_dao constructor param + initializer to match the
  struct declaration (between tag_dao and knowledge_dao). Update both
  state.rs call sites and populate_knowledge.rs to match.
- Hold face_dao lock once across the library-resolver loop instead of
  reacquiring per iteration.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 17:48:22 -04:00
Cameron Cordes
b64a5bec28 insight-chat: add get_faces_in_photo agentic tool
The LLM had no path to see face_detections data — get_file_tags
returns user-applied tags, but a face that's been detected and bound
to a person via the embedding-cluster auto-bind path doesn't always
have a matching tag. The new tool joins face_detections with persons
by content_hash and returns bound names + bboxes, plus unidentified
faces (so smaller models can count people in the photo without
inferring from a visual description).

Gated on face_detections being non-empty via the same has_any_*
pattern as daily_summaries.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 17:43:16 -04:00
Cameron Cordes
388eb22cd2 Remove full plan file, just keep spec 2026-05-07 17:29:04 -04:00
Cameron Cordes
eef41d4172 thumbnails: align video ffmpeg args with the image path so non-yuvj420p sources work
The bare 'ffmpeg -ss 3 -i in -vframes 1 -f image2 out' command failed on
sources whose decoded pix_fmt isn't yuvj420p (e.g. older Samsung phone
videos in yuv420p). With no -vf filter chain, the decoded frame goes
straight to the mjpeg encoder, which rejects it with 'Non full-range
YUV is non-standard' and exits non-zero.

generate_image_thumbnail_ffmpeg already handles the same class of
source for HEIC/RAW by adding -vf scale=200:-1 -c:v mjpeg — the filter
chain lets ffmpeg auto-insert the pix_fmt converter the encoder needs.
Adopt the same args here. Side benefit: video thumbnails are now 200px
wide on disk, matching image thumbnails (previously full-resolution).

Pre-existing .unsupported sentinels for videos that hit this failure
will need to be deleted manually to retry — they're under
$THUMBNAILS/<lib_id>/.../*.unsupported.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 17:20:05 -04:00
Cameron Cordes
b42acbb3f3 fmt: cargo fmt sweep across drifted files
No behavior change — purely whitespace/line-break cleanup that had
accumulated since the last format run.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 16:42:41 -04:00
Cameron Cordes
2a273a3ed9 thumbnails: stop video failures from re-logging every watcher tick
generate_video_thumbnail used .output().expect(...), which only catches
spawn failure — non-zero ffmpeg exits were silently discarded. With no
thumbnail and no .unsupported sentinel left behind, the watcher
re-detected the file as missing every quick-scan tick and re-logged
"New file detected (missing thumbnail)" forever.

Mirror the image branch: return io::Result, check status.success(),
and write the sentinel from create_thumbnails on failure.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 16:41:24 -04:00
Cameron Cordes
a8433c2e01 insight-chat: document the new system_prompt field in CLAUDE.md
Add system_prompt to the /insights/chat body schema with a one-paragraph
note on the append-vs-amend semantics so future readers find the
contract alongside the rest of the chat-continuation docs.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 15:26:32 -04:00
Cameron Cordes
1cdc0f6eb9 insight-chat: drop the dead SmsApiClient::search_messages wrapper
The post-PR-4 delegation kept it as a convenience for callers that
don't filter by contact, but nothing actually uses it. Delete to clear
the dead_code warning. search_messages_with_contact remains as the
single entry point.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 15:10:31 -04:00
Cameron Cordes
e539c083c9 insight-chat: code-review polish on the tool-gating PR
- search_messages now delegates to search_messages_with_contact(.., None)
  so the two methods share a single HTTP path. Drops the dead-code
  warning and the ~30-line duplication.
- DailySummaryDao gains has_any_summaries (LIMIT 1 existence probe)
  used by current_gate_opts; the SELECT COUNT(*) get_total_summary_count
  added in the prior commit is removed (it had no other caller).
- current_gate_opts doc comment corrected to describe what the probes
  actually do.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 15:07:57 -04:00
Cameron Cordes
f50d32667b insight-chat: ToolGateOpts + per-tool description rewrites
Tools whose backing tables are empty (calendar, location_history,
daily_summaries) drop out of the catalog so the LLM doesn't waste
iteration budget calling them only to receive "no results found".
Vision and apollo gates already existed; this generalizes the pattern.

search_messages gains start_ts/end_ts/contact_id filters (date filter
is a client-side post-filter; SMS-API only accepts contact_id natively
on the search endpoint).

Descriptions follow a consistent convention: one sentence (what +
when), param semantics, examples for tools with non-obvious param
choices. No more all-caps headers, no more identity-prescriptive
language inside descriptions.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:56:58 -04:00
Cameron Cordes
b02da0d0cc insight-chat: code-review polish on the days_radius fix
- Bind effective_radius once in fetch_messages_for_contact so the log
  output and window math share a single source of truth for the clamp.
- Clamp tool-supplied days_radius to [1, 30] at the tool boundary so a
  runaway LLM value can't produce a thousand-day window.
- Split the negative-input test into a real negative-input case
  alongside the zero-input case.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:47:46 -04:00
Cameron Cordes
659e7bd973 insight-chat: get_sms_messages tool now honors days_radius
The agentic tool definition advertised a days_radius parameter but
sms_client::fetch_messages_for_contact was hardcoded to ±4 days,
silently ignoring whatever value the LLM chose. Plumb the parameter
through; default 4 retained at the tool level for back-compat.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:42:42 -04:00
Cameron Cordes
428f24b0f8 insight-chat: code-review polish on the chat system_prompt override
- Trim the override input once via Option::map(str::trim).filter(...).
- Use matches!() in restore_system_prompt_override's Prepended arm so
  it reads consistently with the Replaced arm.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:40:04 -04:00
Cameron Cordes
faa289882f insight-chat: per-turn system_prompt override on chat continuation
Append mode: applied ephemerally — original system message restored
before persistence so re-opens see the baked persona. Amend mode:
override stays in place and becomes the new insight row's system
message. Pattern mirrors annotate_system_with_budget.

Adds system_prompt field on both ChatTurnHttpRequest and ChatTurnRequest;
plumbs through chat_turn and chat_turn_stream identically.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:34:08 -04:00
Cameron Cordes
177187f6a2 insight-chat: code-review polish on the system-prompt split
- Use Option::map instead of manual match-on-Option (drops clippy::manual_map).
- Drop redundant `max_iterations = max_iterations` from the format! call.
- Use captured identifiers consistently in the user_content format!.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:27:59 -04:00
Cameron Cordes
8ae4099d46 insight-chat: split generation system prompt into identity + procedural blocks
The framework no longer asserts "you are a personal photo memory
assistant" alongside a user-supplied custom_system_prompt — the
persona is the authoritative identity. The procedural block (tool-use
guidance, iteration budget) stays identity-free.

The user message also stops asking for "a detailed insight with a
title and summary" since the title is regenerated post-hoc anyway and
the wording was constraining voice for no data-model benefit.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:20:45 -04:00
Cameron Cordes
204428b0c0 insight-chat: implementation plan for the spec
Five sequenced PRs:
  1. Split generation system prompt + neutralize user message
  2. system_prompt field on chat request (ephemeral / amend-persisted)
  3. fetch_messages_for_contact honors days_radius
  4. ToolGateOpts + per-tool description rewrites + search_messages
     gains start_ts/end_ts/contact_id
  5. FileViewer-React: persona system_prompt on every turn + style note

Each PR independently mergeable. Tests inline TDD per task.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:15:09 -04:00
Cameron Cordes
fbece0ba9a insight-chat: design for tool catalog, system prompt, and SMS fixes
Lays out the cycle: split generation system prompt into identity vs
procedural blocks so personas drive voice/shape, add per-turn
system_prompt override on chat (ephemeral in append mode, persisted
on amend), gate optional tools on data presence, and fix the
days_radius bug in get_sms_messages.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 14:04:07 -04:00
22e157411c Merge pull request 'date_resolver: drop -fast2 so MP4 moov-at-end files resolve' (#82) from fix/exiftool-mp4-moov-trailer into master
Reviewed-on: #82
2026-05-07 16:42:08 +00:00
Cameron Cordes
c128596470 date_resolver: drop -fast2 so MP4 moov-at-end files resolve
For QuickTime/MP4 files whose `moov` atom sits at the end of the
file (non-faststart — common for Snapchat exports and any MP4
muxed without `-movflags +faststart`), `-fast2` causes exiftool
to skip the trailer and return no `CreateDate` /
`MediaCreateDate`, dropping the resolver to the `fs_time`
fallback for files that actually have a real capture date.

Reported cases:
  Snapchat-477624257.mp4
    fs_time: 2026-05-04 (today, file was just modified)
    real:    QuickTime CreateDate 2018-09-02
  action_compound_cc92e65b709d1deb895b4c2a9484fc6a.mp4
    fs_time: 2026-05-04
    real:    MediaCreateDate 2018-03-01

The waterfall pre-filters to files kamadak-exif couldn't read, so
the JPEG fast-path is already covered without `-fast2`. Paying
full-scan cost on the residual is the right trade. The per-tick
drain re-resolves `source = 'fs_time'` rows, so existing rows
recover automatically on the next watcher tick after deploy — no
SQL migration needed.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 12:40:50 -04:00
ac8d17fb22 Merge pull request 'memories: deny Snapchat-prefixed filenames from timestamp parsing' (#81) from feature/filename-date-snapchat-denylist into master
Reviewed-on: #81
2026-05-07 16:20:06 +00:00
Cameron Cordes
43f8f83d80 memories: deny Snapchat-prefixed filenames from timestamp parsing
Snapchat assigns sequential IDs that happen to overlap real epoch
values, so the 10-16 digit timestamp regex matched and produced
2002-era dates for files actually saved in 2016/2021. The digits
themselves are indistinguishable from a unix timestamp, so we
dispatch on the source-app prefix instead. Case-insensitive,
extensible for future apps that exhibit the same pattern.

Reported cases:
  Snapchat-1021849065.mp4          → 2002-05-19 (actual 2021)
  Snapchat-1751031586660373917.jpg → 2002-09-09 (actual 2016)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 12:17:40 -04:00
e55f6a5961 Merge pull request 'memories: reject implausible filename-derived timestamps' (#80) from feature/filename-date-plausibility into master
Reviewed-on: #80
2026-05-07 16:02:50 +00:00
Cameron Cordes
feaae9b6d3 memories: reject implausible filename-derived timestamps
Filenames like `000227580005.jpg` (film-scan ID) and
`IMG_21323906751390.jpeg` were matched by the 10-16 digit timestamp
regex and resolved to 1970 / 2037, then written into
`image_exif.date_taken` with `source = 'filename'`. EXIF-less
photos showed up under those bogus dates everywhere date_taken is
read.

Two new guards in `extract_date_from_filename`:
- leading zero → reject (real epoch values don't have one at any
  sane resolution).
- resolved year outside [1995, now+1y] → reject.

Both let the date_resolver waterfall fall through to fs_time,
which is a much better proxy for content age than a fake epoch
date. Regression tests cover the two reported filenames.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 12:02:07 -04:00
95e21c8128 Merge pull request 'feature/manual-date-override' (#79) from feature/manual-date-override into master
Reviewed-on: #79
2026-05-07 15:10:37 +00:00
Cameron Cordes
7e1c4ab318 backfill_date_taken: surface the actual diesel error in warnings
The DAO swallowed every diesel::update failure as a flat
`anyhow!("Update error")`, then trace_db_call further reduced it to
`DbError { kind: UpdateError }`. Operators saw "update failed for lib
2 Snapchat/foo.mp4: DbError { kind: UpdateError }" with no clue why
(constraint violation? type mismatch? row vanished mid-flight? DB
locked?).

Two changes:
- Preserve the diesel error in the anyhow chain along with the input
  params (lib, rel_path, date_taken, source) so the cause is visible.
- Log the chain at warn-level inside the DAO before the trace wrapper
  collapses it to DbErrorKind::UpdateError, so the warning at the
  call site finally has something diagnosable next to it.
- Treat zero-row updates as a debug-level "row likely retired by the
  missing-file scan" rather than a hard failure — that case is benign
  and shouldn't poison the drain's error tally.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 11:07:17 -04:00
Cameron Cordes
65af7d999e memories: parse filename dates as UTC, not server local
`extract_date_from_filename` was calling `Local::from_local_datetime`
on the parsed YYYY-MM-DD-HH-MM-SS components, then `.timestamp()` was
shifting the result by the SERVER's TZ offset to produce real UTC
seconds. That made filename-sourced timestamps disagree with EXIF-
sourced timestamps by hours: kamadak-exif's `DateTimeOriginal` is a
naive string parsed AS-IF-UTC (the project's load-bearing
"naive local reinterpreted as UTC" convention), and Apollo's photo
matcher re-anchors that naive value through the BROWSER's TZ when
matching to the track. Anything stamped in server-local instead got
double-shifted on its way through the matcher and through any
`formatNaive*` display path on the client.

Visible symptom in the Apollo DETAILS modal: a photo's CURRENT date
read correctly (1:25 AM via exif) while FROM FILENAME read 4 hours
ahead (5:25 AM in EDT) for the same `IMG_20160710_012515.jpg`.

Switch to `Utc::from_utc_datetime` so `.timestamp()` returns the
wall-clock-as-UTC unix seconds — same convention as the EXIF path.
The /memories endpoint, the canonical-date waterfall (which feeds
`image_exif.date_taken` for filename-only files), and Apollo's
DETAILS modal `filename_date` field all now line up.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 20:43:18 -04:00
Cameron Cordes
16d6586b7d exif: GET /image/exif/full — exiftool dump for the DETAILS modal
The curated `image_exif` columns are a small slice of what exiftool
can read (camera/lens/GPS/capture/dates). Apollo's DETAILS modal wants
to surface everything — white balance, metering, MakerNotes, IPTC,
ICC profile, Composite tags, the lot — for an operator inspecting a
photo's provenance.

`read_full_exif_via_exiftool(path)` shells out to `exiftool -j -G -n`:
JSON output, group-prefixed keys (`EXIF:Make`, `MakerNotes:LensInfo`),
numeric values (callers can reformat). Spawned via web::block to keep
it off the actix worker — RAW with rich MakerNotes can take a few
seconds.

The endpoint is on-demand only; the indexer / file watcher does NOT
call it. Falls back to 503 with a clear message when exiftool isn't
on PATH so Apollo can render an "install exiftool" hint. Multi-library
union resolution mirrors set_image_gps / get_file_metadata.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 19:42:41 -04:00
Cameron Cordes
832b50d587 image_exif: manual date_taken override (set/clear endpoints)
Add `POST /image/exif/date` and `POST /image/exif/date/clear` so an
operator can correct a row whose canonical-date waterfall landed on the
wrong value (camera clock reset, fs_time fallback for a copied-from-
backup file, etc). New `original_date_taken` / `original_date_taken_source`
columns snapshot the prior value on first override so revert is lossless.

The waterfall source set is now `'exif' | 'exiftool' | 'filename' | 'fs_time' | 'manual'`.
The existing `idx_image_exif_date_backfill` partial index already filters
to `date_taken IS NULL OR date_taken_source = 'fs_time'`, so manual rows
are naturally excluded from the per-tick drain — no index change needed.

`ExifMetadata` now exposes `date_taken_source` + originals so a UI can
render "manually set; was X via filename".

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 19:26:43 -04:00
2acc525e73 Merge pull request 'otel: revert HTTP transport, keep gRPC' (#78) from fix/otlp-revert-to-grpc into master
Reviewed-on: #78
2026-05-06 22:36:09 +00:00
Cameron Cordes
ecd49fd053 otel: revert HTTP transport, keep gRPC
The HTTP/protobuf exporter never sent any traffic in prod (tcpdump
on port 4318 showed nothing) despite the receiver path being correct
and the bridge wiring being intact (logs reached journalctl via the
stdout exporter). Likely the BatchLogProcessor + reqwest-client combo
isn't getting the right runtime context, but debugging that on a live
deployment isn't worth holding up the rest of the speedups.

Restoring grpc-tonic transport so prod observability comes back. The
remaining build-time wins on this branch (mold linker, system sqlite3,
profile.dev tweaks, lockfile-only dep refresh) deliver most of the
original savings without touching telemetry. Operator: revert
OTLP_OTLS_ENDPOINT in prod from port 4318 back to 4317.

HTTP transport remains a viable follow-up — needs to be debugged
against a local SigNoz instance with internal SDK error visibility
enabled, on its own branch.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 18:33:37 -04:00
c7bd2226cc Merge pull request 'build: speed up debug compile loop' (#77) from feature/build-time-speedups into master
Reviewed-on: #77
2026-05-06 21:41:19 +00:00
Cameron Cordes
f73db58771 build: speed up debug compile loop
- Drop libsqlite3-sys 'bundled' on Linux/macOS so the SQLite C source
  isn't recompiled every clean build; Windows keeps 'bundled' via a
  cfg(windows) target override.
- Switch opentelemetry-otlp from grpc-tonic to http-proto + reqwest-client.
  Removes the tonic + h2 + hyper-h2 stack from the build graph; reqwest
  was already a dependency. Updates otel.rs to call .with_http().
- Add [profile.dev] debug = "line-tables-only" to shrink linker work
  while keeping panics/backtraces useful.
- Add .cargo/config.toml selecting mold via gcc on x86_64-linux-gnu.
  Requires `apt install mold`. Other platforms use the default linker.
- cargo update: lockfile-only refresh of all minor/patch bumps within
  existing version constraints.

Cold debug build: ~1m 37s; touch-one-file rebuild: ~5s on Linux.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 17:36:42 -04:00
06fdcadf67 Merge pull request 'feature/canonical-date-taken' (#76) from feature/canonical-date-taken into master
Reviewed-on: #76
2026-05-06 21:15:57 +00:00
Cameron Cordes
9f1b3f6d9a date_taken_source: backfill 'exif' on legacy rows
Pre-resolver rows already had a populated `date_taken` from the old
kamadak-exif-only ingest path. The column-add migration left their
`date_taken_source` as NULL, and the drain's eligibility predicate
(`date_taken IS NULL OR date_taken_source = 'fs_time'`) skips them —
so they remain unlabelled forever and never benefit from the
resolver's exiftool fallback even if they're videos that should
upgrade.

Label them all `'exif'` in a one-shot UPDATE. Safe because every
write path that populated `date_taken` before the resolver landed was
a kamadak-exif read. Idempotent (the WHERE matches nothing on a
second run). Down.sql is a no-op — the labels stay correct under any
schema state, and the column-add migration is the right place to
revert if needed.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 17:05:00 -04:00
Cameron Cordes
7f12890f4b memories: single-SQL rewrite + 20-year lookback
Replaces the EXIF-loop + WalkDir-fallback pipeline that powered
`/memories` with a single per-library SQL query
(`get_memories_in_window`) that uses `strftime('%m-%d' | '%W' | '%m',
date_taken, 'unixepoch', tz_offset)` for calendar matching in the
client's timezone, plus a `years_back` lower bound and a
no-future-dates upper bound. Returns only the matching rows; the
handler applies per-library `PathExcluder` post-query and sorts.

Drops:
- `collect_exif_memories` — replaced by the single SQL query.
- `collect_filesystem_memories` — the canonical-date pipeline now
  populates `date_taken` for every row at ingest, so the WalkDir
  fallback that scanned 14k+ files each request is no longer needed.
- `get_memory_date_with_priority` and friends — request-time waterfall
  superseded by `date_resolver` running at ingest. The associated
  three priority-tests are dropped; their replacement lives in
  `date_resolver::tests`.

On a ~14k-file library this drops `/memories` from 10–15 s
(dominated by `fs::metadata` per row) to single-digit ms.

Bumps `DEFAULT_YEARS_BACK` from 15 → 20 to surface deeper archives
on matching anniversaries.

Note vs. ISO weeks: the original Rust used `chrono::iso_week().week()`
for week-span matching. SQLite's `%W` is Monday-anchored but uses week
0 for days before the first Monday, so it can disagree with ISO at
year boundaries by ±1. Acceptable for nostalgia browsing.

Adds 3 new DAO tests covering month-span filter, library scoping, and
the unknown-span-token guard. Also adds a CLAUDE.md section describing
the canonical-date pipeline end-to-end and the new
`DATE_BACKFILL_MAX_PER_TICK` env var.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 16:04:09 -04:00
Cameron Cordes
54e0635a98 date_backfill: per-tick drain for unresolved date_taken rows
Adds two ExifDao methods (`get_rows_needing_date_backfill` /
`backfill_date_taken`) and a `backfill_missing_date_taken` watcher pass
that runs on every tick alongside `backfill_unhashed_backlog`.

The drain queries the partial index for rows where `date_taken IS NULL`
or `date_taken_source = 'fs_time'`, batches up to
`DATE_BACKFILL_MAX_PER_TICK` paths (default 500), and feeds them through
`date_resolver::resolve_dates_batch` — a single exiftool subprocess
covers the whole tick. Rows that newly resolve to `exiftool` /
`filename` / `fs_time` get persisted via `backfill_date_taken` (touches
only `date_taken` + `date_taken_source` so EXIF / hash / perceptual
columns survive).

`filename`-sourced rows are intentionally not re-resolved — the regex
is authoritative when it matches and re-running exiftool wouldn't
change the answer. Files that have disappeared from disk are skipped
so a ghost row doesn't loop through the drain forever; the
missing-file scan in `library_maintenance` retires those separately.

Comes with two DAO unit tests (eligibility filter + column-isolation).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 16:03:03 -04:00
Cameron Cordes
2d14291733 ingest: stamp canonical date_taken on every InsertImageExif
Wires `date_resolver::resolve_date_taken` into the three call sites
that build `InsertImageExif`:

- `process_new_files` (file watcher) — every newly-registered file gets
  the resolver's verdict so videos and EXIF-stripped images land with a
  real date instead of NULL.
- Upload handler — same waterfall on the post-multipart-write path.
- GPS-write handler — re-runs the waterfall after exiftool writes GPS
  and re-reads the EXIF, in case a previously fs_time-sourced row now
  has a real EXIF date to upgrade to.

This is a behavior change vs. the pre-rewrite `/memories` request-time
priority: EXIF now beats filename when both are present. A photo
named `Screenshot_2014-06-01.png` whose EXIF `DateTime` is 2021 now
appears under 2021. The reverse case (no EXIF, parseable filename) is
unchanged and continues to surface the filename date with
`date_taken_source = 'filename'`.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 16:00:14 -04:00
Cameron Cordes
79e258eccd date_resolver: canonical date_taken waterfall with exiftool fallback
New module that consolidates the four-step ingest waterfall:
kamadak-exif (already in process via the caller's prior result) →
exiftool fallback → filename regex → earliest_fs_time. Each step is
tagged with a `DateSource` so the caller can persist provenance.

The exiftool fallback is what makes videos and MakerNote-hosted dates
land at all — kamadak-exif can't read QuickTime/MP4 or Nikon-style
sub-IFDs. Single-file mode shells out per call; batch mode pipes paths
on stdin via `-@ -` and fans the result through one subprocess so the
upcoming per-tick drain doesn't pay startup cost per row. The
`exiftool` PATH check is cached in a `OnceLock` to keep the drain
short-circuited on deploys without exiftool installed.

`SubSecDateTimeOriginal` and `ContentCreateDate` are pulled alongside
the standard tags to capture iPhone's sub-second precision and Apple's
preferred capture-time tag respectively. `FileModifyDate` is
deliberately *not* in the tag list — it's a filesystem-derived value
the resolver already covers via the `fs_time` step, and pulling it
through exiftool would mask "no real EXIF date" with a misleading
`source = exiftool` row.

Module is registered in both `lib.rs` and `main.rs` (sibling-module
pattern the rest of the bin uses); no callers wired in yet — that
lands in the next commit. Comes with 9 unit tests covering JSON
parsing edge cases, source-priority short-circuiting, and the
fs_time-when-no-exif path.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 15:59:02 -04:00
Cameron Cordes
84326501a9 image_exif: add date_taken_source column
New nullable TEXT column tracks which step of the canonical-date
waterfall (kamadak-exif → exiftool → filename → fs_time) populated
`date_taken`. Lets a later per-tick drain re-resolve weak sources
(`fs_time`) once stronger ones become available, and gives the UI/debug
surface a way to answer "why does this photo show up under this date?".

Adds the column at all `InsertImageExif` construction sites with `None`
placeholders (the resolver wiring lands in a follow-up commit), and
extends the `update_exif` SET tuple so the column survives the GPS-write
re-read path. Partial index `idx_image_exif_date_backfill` is created
for the upcoming drain query.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 15:57:49 -04:00
5de9a322ac Merge pull request 'duplicates: folder-pair view of exact dups' (#75) from feature/folder-pair-duplicates into master
Reviewed-on: #75
2026-05-06 18:27:12 +00:00
Cameron Cordes
67cf0c7f73 duplicates: folder-pair view of exact dups
Bucket exact-dup rows by (library_id, dirname) pair on each side, then
filter by coverage = shared / min(folder_a_total, folder_b_total) and
an absolute floor on shared count. Surfaces "this folder is mostly
contained in that folder" matches that the per-file EXACT view buries
under one row each — e.g. an old phone-backup tree shadowing the
organized library, or a topic-grouped folder duplicating a date-grouped
one within the same library.

New endpoint: GET /duplicates/folder-pairs?library=&include_resolved=
&min_coverage=&min_shared=. Cached 5 min keyed on (library, include_resolved);
the user-tunable thresholds filter the cached unfiltered pair list so
slider drags don't re-bucket. Shares the resolve / unresolve flow with
the existing tabs — the frontend fans out N parallel /resolve calls,
one per shared content_hash.

Folder names carry no signal (BMW lives under Night Photos, not BMW_backup),
so bucketing is purely on (library_id, dirname) co-occurrence in
exact-dup groups. Within-folder dups (same hash twice in the same
folder) are skipped — those belong to the EXACT tab.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 12:43:29 -04:00
9ccb48233f Merge pull request 'exif: preserve filesystem mtime on GPS write' (#74) from fix/exif-preserve-mtime into master
Reviewed-on: #74
2026-05-04 20:12:08 +00:00
Cameron Cordes
1ddbca3413 exif: preserve filesystem mtime on GPS write
Pass -P to exiftool so write_gps doesn't bump the file's modification
time. For phone photos with no embedded EXIF datetime, the filesystem
mtime is often the only timestamp we have — losing it on every GPS
backfill would be data loss.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-04 16:09:21 -04:00
82dd21b205 Merge pull request 'feature/duplicate-detection' (#73) from feature/duplicate-detection into master
Reviewed-on: #73
2026-05-03 22:34:49 +00:00
Cameron Cordes
57b7bad086 duplicates: library-aware visibility — only hide a demoted row when its survivor is reachable
Soft-marked rows used to disappear from /photos globally, including
from a library-scoped view that didn't contain the survivor at all.
A user browsing lib A who'd promoted a file from lib B as the
survivor would silently lose visibility on their own copy in lib A,
even though lib B's file isn't reachable from lib A's view.

Library-scoped queries now keep a demoted row visible when its
survivor lives in a library outside the current scope. Implemented
as a NOT EXISTS subquery against the same image_exif table aliased
as `survivor`. The unscoped (all-libraries) view is unchanged — every
survivor is reachable, so demoted rows stay hidden as before.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 18:24:07 -04:00
Cameron Cordes
98057c98a1 duplicates: tighten perceptual cluster — entropy band, asymmetric dHash, medoid prune
Three changes against "still too loose at lowest sensitivity":

- Popcount entropy band tightened from [8, 56] to [16, 48]. The wider
  band let too much low-frequency content through (skies, scans,
  faded film) where pHash collapses to near-uniform values that
  Hamming-trivially across hundreds of unrelated images.
- dHash check now uses an asymmetric stricter threshold
  (dhash_threshold = max(2, threshold/2)). pHash is the candidate-
  discovery signal; dHash is validation. Splitting the budget means
  a real near-dup survives both while incidental pHash collisions
  on uniform content get vetoed. Missing dHash on either side now
  rejects the edge (was: trust pHash alone).
- Single-link union-find can chain weakly-similar images via
  transitive edges. Added a medoid-validation pass: per cluster,
  pick the member with smallest summed distance to others, then
  drop any whose distance to it exceeds threshold. Two new tests
  pin both invariants.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 18:19:48 -04:00
Cameron Cordes
7ca888e95d duplicates: filter low-entropy hashes + dHash double-check, fix backfill loop
The perceptual cluster was producing one giant first group that
contained hundreds of unrelated images. Two causes:
- Solid-colour images (skies, black frames, monochrome scans) all
  hash to near-zero pHashes that Hamming-distance-zero to each other.
- Single-link clustering on pHash alone is too permissive — a chain
  of weakly-similar images all collapses into one cluster.

Fixed by skipping hashes outside the popcount [8, 56] band (uniform
content) and requiring dHash agreement within threshold before
unioning a candidate edge from the BK-tree. Two new tests pin both
invariants.

Backfill bin separately fix: decode-failed rows kept phash_64=NULL
and got re-pulled by every batch, infinite-looping on a queue of
unbreakable formats. Persist a 0/0 sentinel on decode failure so
the row leaves the candidate set; the all-zero hash is excluded
from clustering by the same entropy filter so it doesn't pollute
results.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 18:08:05 -04:00
Cameron Cordes
7584cd8792 duplicates: perceptual hash + soft-mark resolution + upload 409
Adds pHash + dHash columns alongside the existing blake3 content_hash so
near-duplicates (re-encoded, resized, format-converted copies) become
queryable. /duplicates/{exact,perceptual} return groups; /duplicates/
{resolve,unresolve} flip a duplicate_of_hash soft-mark on losing rows
and union perceptual-only tag sets onto the survivor. The default
/photos listing filters duplicate_of_hash IS NULL so demoted siblings
stop cluttering the grid; include_duplicates=true opts back in for
Apollo's review modal. Upload now hashes bytes pre-write and returns
409 with the canonical sibling when a file's bytes already exist.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 17:36:01 -04:00
4340b164eb Merge pull request 'perf/faces-embeddings-no-clone' (#72) from perf/faces-embeddings-no-clone into master
Reviewed-on: #72
2026-05-01 23:09:22 +00:00
Cameron Cordes
fb4df4b195 style: cargo fmt sweep
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 19:01:00 -04:00
Cameron Cordes
1d9b9a0bc4 faces: avoid 40 MB row clone in /faces/embeddings
list_embeddings cloned the full FaceDetectionRow inside the filter_map
just to pair it with the base64-encoded embedding. The 2 KB BLOB was
already on the row — at 20k unassigned faces that's 40 MB of pointless
heap traffic per Apollo cluster-suggest run. Move the bytes out via
Option::take() so the row drops the BLOB instead of duplicating it.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 19:00:55 -04:00
7998a0c9b0 Merge pull request 'feature/per-library-excluded-dirs' (#71) from feature/per-library-excluded-dirs into master
Reviewed-on: #71
2026-05-01 20:11:10 +00:00
Cameron Cordes
58f010f302 docs(claude): pin excluded_dirs entry-form syntax
The two entry shapes for libraries.excluded_dirs / EXCLUDED_DIRS
are not symmetric:
  - /sub/path → multi-segment, library-root-anchored, recursive
  - name     → single component anywhere in the tree

Without this pinned, a reasonable read of the column doc would be
"any path-like string works" — but a multi-segment string without a
leading slash silently never matches (the no-slash form scans path
components for exact string equality, and components are
slash-free).

No code change; just documentation.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 20:05:58 +00:00
Cameron Cordes
814066551e multi-library: per-library excluded_dirs
Adds a nullable comma-separated TEXT column to the libraries table.
Effective excludes for a walk = (env-var globals) ∪
(library.excluded_dirs). Empty / NULL = no library-specific
extras; the global env var still applies.

Migration (2026-05-01-110000_libraries_excluded_dirs)

  ALTER TABLE libraries ADD COLUMN excluded_dirs TEXT. NULL on every
  existing row — no behavior change on upgrade.

Library struct + helpers (libraries.rs)

  - Library gains excluded_dirs: Vec<String>, parsed from the column
    by parse_excluded_dirs_column (drops empties / whitespace,
    matches the env-var parser).
  - Library::effective_excluded_dirs(globals) returns the union.
  - From<LibraryRow> hydrates the field on AppState construction so
    /libraries surfaces it.

Watcher / walkers / memories

  Every per-library walker now consults the effective set:
    - process_new_files (file-watch ingest, RAW/EXIF/face)
    - process_face_backlog (filter_excluded inherits)
    - create_thumbnails (startup + new-file branch)
    - update_media_counts (Prometheus gauge)
    - cleanup_orphaned_playlists (per-library source-existence check)
    - memories endpoint (PathExcluder)

  Effective set is computed once per per-library iteration in the
  watcher tick and threaded through; called functions retain their
  flat &[String] signature (no per-library awareness needed inside
  the walker primitives).

Use case: mount a parent directory while a sibling library covers
a child subtree, and exclude the child subtree from the parent so
the libraries don't double-walk / double-write image_exif. With
hash-keyed derived data (Branches B/C), the duplication-avoidance
is the only cost prevented — face / tag / insight sharing was
already correct via content_hash.

Tests: 228 pass (226 from previous + 2 new in libraries::tests:
parse_excluded_dirs_column edge cases,
effective_excluded_dirs_unions_global_and_per_library).

CLAUDE.md gains a "Per-library excludes" subsection of the
multi-library data model.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 19:54:17 +00:00
4f17af688e Merge pull request 'multi-library: operator kill switch via libraries.enabled' (#70) from feature/library-enabled-flag into master
Reviewed-on: #70
2026-05-01 19:15:20 +00:00
Cameron Cordes
3598bb2cfe multi-library: operator kill switch via libraries.enabled
A small follow-up to Branches A/B/C. Adds a nullable-default-1
boolean column to the `libraries` table that controls whether the
watcher considers the library at all. Useful for staging a new
mount before committing to ingest, and as a maintenance kill
switch when a library needs to be quiet without being unmounted.

Migration (2026-05-01-100000_libraries_enabled_flag)

  ALTER TABLE libraries ADD COLUMN enabled BOOLEAN NOT NULL DEFAULT 1.
  Existing rows stay enabled — no behavior change on upgrade.

Watcher gate (main.rs)

  At the top of the per-library loop, if !lib.enabled { continue; }
  — runs BEFORE the availability probe. Disabled libraries don't
  enter the health map, don't get probed, don't get ingest, don't
  get any maintenance pass. The initial sweep before the loop's
  first sleep also skips disabled libraries.

Orphan-GC consensus (library_maintenance.rs)

  all_libraries_online filters disabled libraries out of the
  consensus check — they're treated as out-of-scope, not as
  blockers. Otherwise flipping enabled=false would permanently
  halt orphan GC for the rest of the system, which is the opposite
  of the intended kill-switch semantics.

Cross-library duplicates: safe by construction. Hash-keyed derived
data (face_detections, tagged_photo with hash, photo_insights with
hash) is anchored by ANY image_exif row carrying the hash. Disabling
a library does NOT delete its image_exif rows, so a hash referenced
by a disabled library's row stays anchored — derived data survives.
collect_orphan_hashes deliberately doesn't filter image_exif by
library.enabled for exactly this reason.

No HTTP endpoint. Library mutation is rare-enough infra work that a
SQL toggle is fine, and a public mutation endpoint without a role /
permission story would be poorly-prioritized exposure for a
single-user tool. Documented in CLAUDE.md.

Tests: 226 pass (225 from Branch C + 1 new
all_libraries_online_treats_disabled_as_out_of_scope, which proves
that even an explicit Stale entry on a disabled library doesn't
block the consensus).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 19:10:24 +00:00
23448cf5e6 Merge pull request 'feature/library-handoff-and-gc' (#69) from feature/library-handoff-and-gc into master
Reviewed-on: #69
2026-05-01 18:27:40 +00:00
Cameron Cordes
d809ddee44 library_maintenance: clarify orphan-gc log wording
"marked 2 new" parses as "2 new files" on first read — but the
unit is content_hashes, and the action is observing them as
orphaned (becoming-deleted, not appearing). Reword:

  "{} new orphan hash(es) marked, {} revived"

instead of "marked {} new, revived {}". Also pluralize the deleted
counts ("row(s)") and append the pending-set size to the success
log so a tick that both deletes and re-marks doesn't lose the
trailing-state context.

No behavior change.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 18:01:01 +00:00
Cameron Cordes
fa98d147be library_maintenance: log orphan-gc decisions in stale-library path too
run_orphan_gc returned early on the !all_online branch before the
final debug/info log line, so the GC was effectively invisible
whenever any library was Stale — exactly the dry-run scenario where
operators most want to confirm the safety gate is firing. Add the
same conditional log inside the early-return branch (plus a
"deferred — at least one library Stale" hint in the info-level
variant when there's something newly marked).

No behavior change beyond observability.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 17:14:09 +00:00
Cameron Cordes
5f247be1f1 docs(claude): note in-place edit gap as future Branch D
The maintenance pipeline added in Branch C assumes (library_id,
rel_path) bytes are stable for as long as the file lives at that
path. In-place edits (crop, re-export to same name) bypass
process_new_files's already-indexed check, so the row's
content_hash stays pinned to the original bytes — tags / faces /
insights remain attached to that hash silently.

Document the gap and the proposed shape of the fix:
  - Stale-content detection pass: compare last_modified / size_bytes
    to fs::metadata, re-hash on mismatch, update image_exif.
  - "Content branched" semantics on hash change: faces re-run, tags
    migrate forward (user intent survives a crop), insights migrate
    + flag for re-generation, favorites follow path.
  - Apollo derived.db cache invalidation belongs in the same design
    cycle, not after.

Captured here so the design intent is clear before someone hits the
case in real life. No code change.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 16:53:08 +00:00
Cameron Cordes
263e27e108 multi-library: handoff + orphan GC with two-tick consensus
Branch C of the multi-library data-model rollout. Implements the
operational maintenance pipeline pinned in CLAUDE.md → "Multi-library
data model" / "Library availability and safety". Branches A and B
land first; this branch builds on top.

New module: src/library_maintenance.rs

Three idempotent passes the watcher runs every tick after the
per-library ingest loop:

1. Missing-file scan (per online library)

   For each Online library, load a paginated page of image_exif rows
   (IMAGE_EXIF_MISSING_SCAN_PAGE_SIZE, default 500), stat() each one,
   and delete rows whose source file is NotFound. Permission/IO
   errors are skipped, never deleted. Capped at
   IMAGE_EXIF_MISSING_DELETE_CAP_PER_TICK (default 200) per library
   per tick — so a pathological mount that returns NotFound for
   everything can't wipe the table in one cycle. Cursor advances
   across ticks, wraps on partial-page returns, and naturally cycles
   through the entire library over many minutes. Skipped wholesale
   for Stale libraries via the existing probe gate.

2. Back-ref refresh (DB-only)

   For face_detections / tagged_photo / photo_insights: any
   hash-keyed row whose (library_id, rel_path) no longer matches an
   image_exif row, but whose content_hash does, is repointed at a
   surviving image_exif location. Pure SQL with EXISTS guards so
   rows whose hash is fully orphaned are left alone (the orphan GC
   handles those). Idempotent; no availability gate needed.

   This is what makes a recent → archive move invisible to readers:
   when pass 1 retires the lib-A row, pass 2 pivots tags / faces /
   insights to lib-B's surviving path before any client notices.

3. Orphan GC (destructive)

   Hash-keyed derived rows whose content_hash has no image_exif
   referent are GC-eligible. Two-tick consensus: a hash must be
   observed orphaned on two consecutive ticks AND every library must
   be Online for both. A single Stale tick within the window cancels
   all pending deletes (they remain marked but won't be promoted) —
   they're re-evaluated next tick. The pending set lives in
   OrphanGcState (in-memory); a watcher restart resets it, which can
   only delay a delete, never cause one. Hashes that re-appear in
   image_exif between ticks are "revived" from the pending set
   (handles transient share unmount / remount).

Two new ExifDao methods:
  - list_rel_paths_for_library_page(library_id, limit, offset) for
    the paginated missing-file scan.
  - (count_for_library landed in Branch A.)

Watcher wiring (main.rs)

Per-library: missing-file scan inside the existing per-library
loop, after process_new_files, gated by the same probe check that
already protects ingest. After the loop: reconcile (Branch B),
back-ref refresh, then run_orphan_gc. The maintenance connection is
opened once per tick (image_api::database::connect), used by all
three DB-only passes, and dropped at end of tick.

CLAUDE.md gains a "Maintenance pipeline" subsection that describes
the three passes and their interaction with the existing
availability-and-safety policy.

Tests: 225 pass (217 from Branch B + 8 new in library_maintenance
covering back-ref refresh including the fully-orphaned no-op case,
two-tick GC consensus, Stale-tick consensus reset, image_exif
re-appearance revival, multi-table delete, and the
all_libraries_online helper).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 16:27:53 +00:00
a0283a6362 Merge pull request 'multi-library: hash-keyed tagged_photo + photo_insights with reconciliation' (#68) from feature/hash-keyed-derived-data into master
Reviewed-on: #68
2026-05-01 16:16:38 +00:00
Cameron Cordes
48cac8c285 multi-library: hash-keyed tagged_photo + photo_insights with reconciliation
Branch B of the multi-library data-model rollout. tagged_photo and
photo_insights now follow the bytes (content_hash), not the path,
matching the policy pinned in CLAUDE.md "Multi-library data model".
Branch A's availability probe and EXIF scoping land first; this
branch builds on top.

Migration (2026-05-01-000000_hash_keyed_derived_data)

  Adds nullable content_hash columns to tagged_photo and photo_insights,
  with partial indexes on the non-null subset to keep the index small
  during the transitional window. The migration backfills from
  image_exif:
    * tagged_photo joins on rel_path alone (no library_id available);
    * photo_insights joins on (library_id, rel_path), unambiguous.
  Rows whose image_exif hash isn't known yet stay null and the runtime
  reconciliation pass populates them as the hash backlog drains.

Insert-time population

  TagDao::tag_file looks up image_exif.content_hash by rel_path before
  inserting; the hash is written into the new column.
  InsightDao::store_insight does the same scoped to (library_id,
  rel_path). Caller-supplied hash on InsertPhotoInsight wins; otherwise
  the DAO does the lookup. Both paths fall back to None if the hash
  isn't known yet — reconciliation backfills.

Reconciliation (database/reconcile.rs)

  Three idempotent passes the watcher runs once per tick after the
  per-library backfill loop:
    1. tagged_photo NULL hashes → populate from image_exif by rel_path.
    2. photo_insights NULL hashes → populate by (library_id, rel_path).
    3. photo_insights scalar merge — when multiple is_current rows
       share a content_hash, keep the earliest generated_at as
       current; demote the rest. Demoted rows keep their data so
       /insights/history is unaffected; only the "current" pointer
       narrows to one per hash.

  No filesystem dependency, so reconcile doesn't need the availability
  gate; runs every tick. Logs once when something changed, debug
  otherwise.

  Tags are set-valued under the policy (union on read, already
  DISTINCT in queries), so there is no analogous tag-collapse pass —
  duplicate (tag_id, content_hash) rows across libraries are
  harmless.

Read paths are unchanged in this branch — lookup_tags_batch's
existing rel_path-via-hash-sibling expansion still produces the
correct merge. A follow-up can simplify reads to use the new column
directly for performance.

Tests: 217 pass (212 pre-existing + 5 new in reconcile covering
NULL-fill, hash-not-yet-known no-op, library scoping on insights,
earliest-wins collapse, idempotency).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 14:52:16 +00:00
cce8f0c1b7 Merge pull request 'feature/multi-library-data-model' (#67) from feature/multi-library-data-model into master
Reviewed-on: #67
2026-05-01 14:40:16 +00:00
Cameron Cordes
48ed7be5d9 libraries: initial availability sweep before watcher's first sleep
new_health_map seeds every library as Online, and the watcher's tick
loop sleeps WATCH_QUICK_INTERVAL_SECONDS (default 60s) before its
first probe — meaning /libraries reported the optimistic default for
up to a minute after boot, even when a share was clearly unmounted.

Run the same refresh_health pass once at the top of the watcher
thread before entering the sleep loop. /libraries is then truthful
within milliseconds of the watcher thread starting (effectively from
the first HTTP request, since the watcher spawns well before the
server binds).

The per-tick gate inside the loop is unchanged.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 14:33:45 +00:00
Cameron Cordes
eea1bf3181 multi-library: availability probe + scoped EXIF queries + collision fixes
Branch A of the multi-library data-model rollout. Three threads of
correctness/safety work that ship together because the new mount
needs all three before it can land:

1. Library availability probe (libraries.rs, state.rs, main.rs)

   New LibraryHealth (Online | Stale { reason, since }) and a shared
   LibraryHealthMap on AppState. Probe checks root_path exists +
   is_dir + readable + non-empty (relative to a "had_data" signal so
   fresh mounts aren't downgraded). The watcher tick begins with a
   refresh_health() per library; stale libraries skip ingest, the
   hash backfill, and face-detection backlog drains for that tick.
   The orphaned-playlist cleanup also gates on every library being
   online — a missing source on a stale library is indistinguishable
   from a transient unmount, and the cleanup is destructive.

   /libraries now returns each library with its current health
   state. Logs only on Online↔Stale transitions so a long outage
   doesn't spam.

   New ExifDao::count_for_library is the "had_data" signal.

2. EXIF queries scoped by library_id (database/mod.rs, files.rs,
   main.rs, tags.rs)

   query_by_exif gains an Option<i32> library filter; /photos and
   /photos/exif now pass it. Without this, an EXIF-filtered request
   scoped to ?library=N returned cross-library results because the
   handler resolved the library but didn't push it through to SQL.

   get_exif_batch gains the same option. The watcher's per-library
   ingest, face-candidate build, and content-hash backfill all
   scope to their library; the union-mode /photos date-sort path
   and the library-agnostic tag fan-out (lookup_tags_batch, by
   design) keep using None.

3. Derivative-path collision fixes (content_hash.rs, main.rs)

   New content_hash::library_scoped_legacy_path helper:
   <derivative_dir>/<library_id>/<rel_path>. Thumbnail generation
   (startup walk + watcher needs-thumb check) and serving now use
   it; serving falls back to the bare-legacy mirrored path so
   pre-multi-library deployments keep working without
   regeneration. Without this, lib2 with the same rel_path as lib1
   would have its thumbnail request short-circuit to lib1's image.

   Orphaned-playlist cleanup walks every library when checking for
   the source video (was: BASE_PATH only). Without this, mounting
   a 2nd library and waiting 24h would delete every playlist whose
   source lived only in the 2nd library.

   The HLS playlist write path collision (filename-only basename,
   not rel_path) is left as a known issue with a TODO at the call
   site — the actor-pipeline rewrite belongs in Branch B/C.

Tests: 212 pass (cargo test --lib). New tests cover the probe
states (online / missing root / non-dir / empty-with-prior-data),
refresh_health transitions, query_by_exif scoping, get_exif_batch
keying on (library_id, rel_path), library_scoped_legacy_path, and
count_for_library.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 14:12:49 +00:00
Cameron Cordes
2f91891459 docs(claude): pin multi-library data model + availability/safety policy
Adds a "Multi-library data model" section that classifies each table as
intrinsic-to-bytes (hash-keyed), user-intent-about-a-photo (hash-keyed),
or library-administrative ((library_id, rel_path)). Spells out merge
semantics on read (union for set-valued, earliest-wins for scalar),
write attribution (binds to bytes, not to current library), the
transitional-state rules for hash-less rows, library handoff behavior
on archive moves, and orphan GC.

Adds a "Library availability and safety" subsection: every watcher
tick begins with a presence probe; destructive paths (move-handoff
re-keying, orphan GC) require both/all libraries online and
confirmed-clean for two consecutive ticks. A NAS reboot, USB pull, or
VPN drop must never trigger destruction — the worst case is that
derived-data work pauses until the share returns.

The face_detections table is referenced as the existing reference
implementation of the policy.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 14:11:42 +00:00
3d162105f7 Merge pull request 'feature/edit-tag' (#66) from feature/edit-tag into master
Reviewed-on: #66
2026-05-01 01:03:40 +00:00
Cameron
98601973f7 faces: log at the three 503 paths in update_face_handler
PATCH /image/faces/{id} can return 503 from three places (face client
disabled, transient embed error, mid-flight disable) and none of them
were logging — operator sees the status code but nothing in the Rust
log explaining why. Add warn! lines at each so future bbox-edit
failures aren't silent. Response body is unchanged so existing clients
keep working.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 20:57:51 -04:00
Cameron
862917b0d1 gitignore: SQLite WAL runtime + local docs/specs dirs
*.db-shm / *.db-wal show up in the working tree whenever the server
runs (the WAL/journal pragmas in connect()), and /docs and /specs
hold per-feature design notes that stay local per the project's
"spec docs not in git" convention.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 20:31:19 -04:00
Cameron
44d677528e tags: add edit + delete endpoints, enable FK enforcement
PUT /image/tags/{id} renames a tag globally; DELETE /image/tags/{id}
removes a tag and every photo's reference. Rename returns 200/404/409
(case-insensitive name conflict) / 400 (empty name); delete returns
204/404. New migration adds a UNIQUE COLLATE NOCASE index on
tags.name with a pre-flight pass that collapses existing case-
insensitive duplicates onto the lowest id.

The connection setup now sets PRAGMA foreign_keys = ON. The schema
already declares ON DELETE CASCADE / SET NULL on several tables —
those clauses were documentation-only because SQLite has FK
enforcement off per-connection by default. Audited every
diesel::delete site; each touches either no inbound FKs or has a
matching policy. delete_tag relies on the tagged_photo cascade
instead of doing manual cleanup.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 20:26:35 -04:00
89b743ba54 Merge pull request 'faces: count distinct content_hash in stats total_photos' (#65) from face-stats-dedup-hash into master
Reviewed-on: #65
2026-04-30 22:43:58 +00:00
Cameron Cordes
323097c650 faces: count distinct content_hash in stats total_photos
face_detections is keyed on content_hash (one row per unique bytes,
shared across libraries / duplicate paths) but total_photos was
COUNT(*) over image_exif rows. A file present at multiple rel_paths or
across libraries inflated the denominator without inflating the
numerator, leaving a permanent gap (e.g. 1101/1103 with nothing
actually pending detection).

Switch total_photos to COUNT(DISTINCT content_hash) so numerator and
denominator live in the same domain. Exclude rows with NULL
content_hash from the count — they're held in the hash-backfill
backlog, not the detection backlog, and counting them pins the bar
below 100% for the duration of that pass.

CLAUDE.md: document the stats domain rule next to the rest of the
face-detection notes.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 22:41:20 +00:00
d0833177c7 Merge pull request 'feature/face-stats-exclude-videos' (#64) from feature/face-stats-exclude-videos into master
Reviewed-on: #64
2026-04-30 21:17:19 +00:00
Cameron Cordes
67abd8d8ff style: cargo fmt
Pre-existing whitespace drift in test bodies, normalized by rustfmt.
No behavior change.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 21:16:34 +00:00
Cameron Cordes
0840d55c70 faces: exclude videos from backlog drain and SCANNED denominator
list_unscanned_candidates pulled every hashed image_exif row, including
videos. filter_excluded then dropped them client-side without writing a
marker, so the same set re-appeared every watcher tick — emitting the
"backlog drain — running detection on N candidate(s)" log forever and
producing no progress.

face_stats.total_photos counted the same video rows in the denominator,
so the SCANNED percentage was structurally capped below 100%.

Add an image-extension SQL predicate (case-insensitive, sourced from
file_types::IMAGE_EXTENSIONS) and apply it to both queries. Videos
never enter the candidate set, total_photos counts only what can
actually be scanned, and 100% becomes reachable.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 21:16:30 +00:00
dbb046dfa8 Merge pull request 'indexer: prune EXCLUDED_DIRS at WalkDir time, extract enumerate_indexable_files' (#63) from feature/exclude-dirs-at-index-time into master
Reviewed-on: #63
2026-04-30 20:24:18 +00:00
Cameron Cordes
f50655fb21 indexer: apply EXCLUDED_DIRS to remaining WalkDir callers
Audit follow-up to 5bf4956. The same `@eaDir` pruning that protects
the indexer also needs to protect the other walks under library roots:

- `create_thumbnails` walks every file in every library to generate
  thumbnails. Without EXCLUDED_DIRS, it would generate thumbnails of
  Synology's `SYNOFILE_THUMB_*.jpg` thumbnails (thumbnails of thumbnails).
- `update_media_counts` walks for the prometheus IMAGE / VIDEO gauges.
  Without EXCLUDED_DIRS, the gauges over-count by however many phantom
  `@eaDir` images live alongside the real photos.
- `cleanup_orphaned_playlists` walks BASE_PATH searching for source
  videos by filename. EXCLUDED_DIRS isn't a behavior change for typical
  Synology mounts (no .mp4 in @eaDir), but it's a correctness win for
  any operator-defined exclude that happens to contain video.

Refactor: add `walk_library_files(base, excluded_dirs) -> Vec<DirEntry>`
to file_scan.rs as the shared primitive. `enumerate_indexable_files`
now layers media-type + mtime filters on top of it. One new test
covers the lower-level helper (returns all extensions, prunes excluded
subtrees).

`generate_video_gifs` (currently `#[allow(dead_code)]`, not reachable
from main) gets the `update_media_counts` signature update and reads
EXCLUDED_DIRS from env so a future revival isn't broken — but its
WalkDir walk stays raw because the dual lib/bin compile makes the
file_scan module path non-trivial there. Tagged with a comment.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 20:21:17 +00:00
Cameron Cordes
5bf49568f1 indexer: prune EXCLUDED_DIRS at WalkDir time, extract enumerate_indexable_files
Synology drops `@eaDir/.../SYNOFILE_THUMB_*.jpg` files alongside every
photo. The face-detect pipeline already filters those out via
`face_watch::filter_excluded`, but the filter runs *after* the indexer
has already inserted rows into `image_exif`. Result: phantom rows whose
content_hash never matches a `face_detections` row, so the anti-join in
`list_unscanned_candidates` returns them every tick. They're filtered
out at runtime, no marker is written, and the cycle repeats forever —
log spam, wrong stats denominator, and on a real Synology library the
phantom rows balloon into the hundreds of thousands.

Move the exclusion to the WalkDir pass, where filter_entry can prune
whole subtrees instead of walking and discarding leaves. Extract the
pre-existing 30-line walker chain in main.rs::process_new_files into
`file_scan::enumerate_indexable_files` so it's testable in isolation.

Six tests cover the bug (eadir prune), nested patterns, absolute-under-base
syntax, non-media filtering, modified_since semantics, and forward-slash
rel_path normalization.

Out of scope (other WalkDir callers in main.rs that don't yet apply
EXCLUDED_DIRS — thumbnail gen at 1309, media scan at 1377, video
playlist scan at 1685, and two nested walks at 1709 / 1743): separate
audit PR.

Operator note: existing phantom rows still need a one-shot cleanup —
  DELETE FROM face_detections WHERE content_hash IN (
    SELECT content_hash FROM image_exif WHERE rel_path LIKE '%/@eaDir/%'
  );
  DELETE FROM image_exif WHERE rel_path LIKE '%/@eaDir/%' OR rel_path LIKE '@eaDir/%';
Run before attaching a fresh Synology-sourced library.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 19:29:37 +00:00
f358e83050 Merge pull request 'sqlite: enable WAL + busy_timeout in connect(); 408/413/429 transient' (#62) from feature/sqlite-wal-and-413-transient into master
Reviewed-on: #62
2026-04-30 18:16:38 +00:00
Cameron Cordes
db9dc63e5e sqlite: enable WAL + busy_timeout in connect(); 408/413/429 transient
The DB connection helper now sets `journal_mode=WAL`, `busy_timeout=5000`,
and `synchronous=NORMAL` on every connection. 13+ DAOs each open their
own connection through this helper and share one SQLite file — without
WAL, a writer's exclusive lock blocks readers and `load_persons` racing
the face-watch write storm errored instantly with "database is locked".
GPU face inference made this visible by speeding detect ~10× and
flooding the writer side. WAL persists in the file once set so the
debug binaries that bypass connect() inherit it automatically.

Also widen face_client.rs's classifier: 408 / 413 / 429 are now Transient
instead of Permanent. These are operator-fixable proxy/infra errors;
marking them Permanent poisons every affected photo with status='failed'
and requires manual SQL to recover. Specifically, Apollo's nginx
defaulted to a 1 MB body cap and silently rejected normal-size photos
before they reached the backend — the deferred-and-retry contract is
the right behavior for that class of fault.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 18:13:15 +00:00
9443c91f88 Merge pull request 'Face Recognition / People Integration' (#61) from feature/face-recog-phase3-file-watch into master
Reviewed-on: #61
2026-04-30 17:22:08 +00:00
Cameron Cordes
96c539764c docs: face detection system section + per-tick backlog drain env vars
CLAUDE.md gets an "Important Patterns → Face detection system" entry
covering the schema (why content_hash and not (library_id, rel_path)),
the file-watch hook + per-tick backlog drains, auto-bind on tag-name
match, manual-face create with EXIF orientation handling, and the
rerun-preserves-manual-rows contract. README's face section adds
the two new env vars (FACE_BACKLOG_MAX_PER_TICK and
FACE_HASH_BACKFILL_MAX_PER_TICK) shipped this cycle so operators
know they're tunable.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 14:06:42 +00:00
Cameron Cordes
675b4a4849 faces: add .env.example template covering all documented env vars
The face-recognition plan and CLAUDE.md document the full env-var
surface (face detection knobs, Apollo / Ollama / OpenRouter / SMS
integrations, watch intervals, RAG flags), but no example file
existed — operators copying the project to a new deploy had nothing
to start from. Group by section, comment out optional integrations
so a minimal copy boots without external services.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 13:51:45 +00:00
Cameron Cordes
5e1bad3179 faces: filter videos out of detection candidate set
The backlog drain pulls every hashed image_exif row, which includes videos.
Sending them to Apollo just produces 422 decode_failed → status='failed'
markers, burning a round-trip per video and inflating the FAILED stat.

Widen filter_excluded to also drop anything is_image_file rejects. Covers
both call sites (file-watch hook and per-tick backlog drain) without
plumbing a second filter through.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 12:45:55 +00:00
Cameron Cordes
1971eeccd6 faces: drain backfill + detection backlog every tick, not just full scans
Symptom: ImageApi restart, then ~60 minutes of silence — no
face_watch lines at all. Cause: backfill + face-detection candidate
build were both gated inside process_new_files, which during quick
scans (every 60s) only walks files modified in the last interval.
The pre-existing unhashed / unscanned backlog never entered the
candidate set, so it only drained on the full-scan path (default
once per hour). Surfaced as "scan stuck at 1101/13118" — most of
those rows were waiting on the next full scan.

Two new per-tick passes that work directly off the DB:

(1) backfill_unhashed_backlog uses ExifDao::get_rows_missing_hash to
    pull unhashed rows in id order, capped (FACE_HASH_BACKFILL_MAX_PER_TICK
    default 2000), and writes content_hash for each. No filesystem
    walk — the walk was the gating filter that hid the backlog.

(2) process_face_backlog uses a new FaceDao::list_unscanned_candidates
    (LEFT-anti-join on content_hash via raw SQL, GROUP BY hash so
    duplicates fire one detect call) to pull a capped batch of
    hashed-but-unscanned rows (FACE_BACKLOG_MAX_PER_TICK default 64)
    and runs the existing face_watch detection pipeline on them.

Both run only when face_client.is_enabled(). The cap on (2) is small
because each candidate is a real Apollo round-trip — 64/tick at 60s
quick interval ≈ 64 detections/min, which paces an 8-core CPU
inference comfortably while keeping a steady flow visible in logs.
process_new_files's own backfill stays in place for the same-tick
flow (a brand-new upload gets hashed AND face-scanned in the tick
where it's discovered) but is now belt-and-suspenders.

Test backstop pinning the new DAO method's filter contract: only
hashed, unscanned, in-library rows are returned; scanned rows,
unhashed rows, and other-library rows are filtered out.
2026-04-30 01:46:49 +00:00
Cameron Cordes
c2c1fe5b8b faces: bbox crop respects EXIF orientation + pads enough for RetinaFace
Two reasons manually-drawn bboxes were never resolving a face on
re-detection:

(1) The bbox arrives in display space (browser already applied EXIF
    orientation when rendering the carousel), but the `image` crate
    in crop_image_to_bbox opens raw pre-rotation pixels. For any
    phone photo with Orientation 6/8/etc., applying the bbox without
    rotating first crops a completely different region of the image
    — landing on background, hair, or empty pixels. Now reads the
    EXIF Orientation tag and applies it before indexing into the
    canonical-oriented dims.

(2) Padding was 10 % on each side. A typical 200×250 face bbox +
    10 % becomes ~240×300; insightface resizes that to det_size=640,
    so the face fills ~95 % of the input. RetinaFace's anchors
    expect faces at 20–60 % of input dimensions; at 95 % it
    routinely returns zero detections. Bumped to 50 % padding so the
    crop is 2× the bbox dims and the face occupies ~50 % of the
    input — anchor-friendly. Bbox is still clamped to image bounds,
    so edge-of-image cases just get less padding on the clipped
    side.

Together these explain why bbox-edit re-embed practically always
fell into the "no face detected" branch (and bbox-edit reverts
without the recent soft-fallback commit). Per-photo embedding
quality also improves slightly — same face, more context, better
landmarks for ArcFace.
2026-04-30 01:06:08 +00:00
Cameron Cordes
5a2f406429 faces: bbox edits survive when re-detection finds no face
Moving a tagged bbox off-center (to fine-tune position, or onto a
back-of-head the operator already manually tagged) made
update_face_handler 422 because the re-embed step ran detection on
the new crop and found nothing. Frontend's catch then reverted the
optimistic update — visible as the bbox snapping back the moment the
user released their drag.

The re-embed is a soft contract: a fresh ArcFace vector is preferable,
but the operator's bbox edit is sacred. Now:

  - empty faces[] → keep old embedding, apply the bbox, log info
  - permanent embed error → keep old embedding, apply the bbox, log info
  - bad-bytes embedding → keep old embedding, apply the bbox, log warn
  - transient failure (cuda_oom, engine unavailable) still 503s so
    the operator can retry — those are recoverable and we don't want
    to silently drift cluster math on retries that succeed later

Cost: a slightly stale embedding for the row, which marginally
affects clustering / auto-bind cosine for files re-detected against
this person. Accepted because dropping the user's manual drag every
time the new crop happens to lose detection is a much worse UX —
especially for the force-create rows (back of head, profile) where
re-detection will *always* fail.
2026-04-30 01:01:07 +00:00
Cameron Cordes
6a6a4a6a46 tags: batch lookup expands content-hash siblings cross-library
The first cut matched by rel_path only — fine for single-library
deploys but wrong for multi-library setups where the same content
lives under different rel_paths (e.g. a backup mount holding copies
of the primary library). A tag applied under library A would silently
not appear in the library-B grid badge even though the carousel's
per-path /image/tags would resolve it correctly via siblings.

The batch handler now does the expansion server-side in three queries
regardless of input size:

  1. image_exif batch lookup → query path → content_hash
  2. image_exif JOIN by content_hash → all sibling rel_paths sharing
     each hash (paths are deduped across libraries)
  3. tagged_photo + tags JOIN over the union of (query + sibling)
     rel_paths

Tags are then aggregated back to query paths via a sibling→originals
reverse map, deduped by tag id. Files without a content_hash (just
indexed, hash compute pending, etc.) skip step 2 and only get tags
from their own rel_path — same fallback the per-path handler uses.

Adds ExifDao::get_rel_paths_for_hashes (batch counterpart of
get_rel_paths_by_hash) chunked at 500 to stay under SQLite's
SQLITE_LIMIT_VARIABLE_NUMBER. Five queries for a 4k-photo grid is
still ~800x cheaper than per-path HTTP fan-out.
2026-04-30 00:36:44 +00:00
Cameron Cordes
3112260dc8 tags: batch lookup endpoint to collapse photo-match fan-out
Apollo's photo-match enrichment fanned out one ``GET /image/tags?path=``
per record (bounded concurrency 20) — for a 4k-photo time window that
meant ~4000 round-trips, each briefly contending the tag-dao mutex.
The cost dwarfed the actual SQL.

Add a single ``POST /image/tags/lookup`` body ``{paths: [...]}``
returning ``{path: [tag, ...]}`` with only paths that have at least
one tag. SqliteTagDao gains ``get_tags_grouped_by_paths`` which JOINs
tagged_photo + tags and chunks the IN clause at 500 (safely under
SQLite's variable limit). Five queries for a 4k-photo grid is ~800x
cheaper than 4k HTTP calls.

Trade-off: the batch matches by rel_path directly and does not do the
cross-library content-hash sibling expansion that the per-path
``GET /image/tags`` does. For Apollo's grid that's accepted as
deliberate — single-library deploys see no difference, multi-library
deploys with rel_path-divergent siblings might miss a tag in the grid
badge but the carousel still resolves full sibling tags via the
per-path endpoint when opened. If sibling sharing in the grid becomes
load-bearing, extend the handler to JOIN image_exif on content_hash.
2026-04-30 00:28:33 +00:00
Cameron Cordes
16abacf4c5 faces: backfill no longer stalls on chronic-error files at the front
The content-hash backfill capped at 500/tick AND counted errors
against that cap. So a pocket of files that errored every time
(vanished mid-scan, permission denied, unreadable) at the head of the
exif_records iteration order burned the entire budget every tick and
the rest of the backlog never advanced — surfacing as a face-scan
stuck at e.g. 44% with no progress. Without a content_hash, those
photos never become face-detection candidates, so it looks like
detection is broken when really it's the prerequisite hash that
isn't filling.

Two fixes:

  - Cap on successes only. Errors still get counted and logged but
    don't burn the per-tick budget; the loop keeps moving past them
    to the working files behind. Errors are bounded by the unhashed
    backlog size (each record walked at most once per tick), so this
    can't run away.

  - Always log the unhashed backlog count when non-zero. Previously
    "stuck at 44%" looked silent from the outside; now every tick
    surfaces "backfilled N/M; K still need backfill" so an operator
    can tell backfill is making progress (or isn't).

Also bumps the default cap from 500 to 2000. Hashing is cheap (blake3
+ one DB UPDATE), and 500 was conservative for a personal-scale
library where 10k+ unhashed files is a normal first-run state.
2026-04-30 00:03:26 +00:00
Cameron Cordes
891a9982ef faces: force-create path for regions the detector can't see
Adds an opt-in 'force' flag to POST /image/faces. When set, the handler
skips the Apollo embed call entirely and stores the row with a
2048-byte zero-vector embedding under the sentinel model_version
'manual_no_embed'. The row participates as a browse-by-person tag but
is excluded from clustering and auto-bind:

- face_clustering._decode_b64_embedding filters norm<=0 (already)
- cluster suggester groups by model_version, so the sentinel never
  mixes with real buffalo_l rows
- cosine_similarity with a zero vector resolves to 0/NaN, never
  crossing the 0.4 auto-bind threshold

Use case: tag someone looking away from the camera, profile shot,
heavily-occluded face — anywhere the detector returns no_face_in_crop
on the user's drawn region. The frontend only sets force=true after a
422 from a strict create plus an explicit operator confirmation, so
the normal "draw a centered face" UX still gets a real ArcFace
embedding.
2026-04-29 23:49:34 +00:00
Cameron Cordes
0eaf27d2d3 faces: cover hydrate_face_with_person — assigned + unassigned branches
Two unit tests pinning the response shape that PATCH/POST /image/faces
relies on. They use the existing in-memory SQLite harness and exercise
the helper directly:

- assigned: person_name resolves through the persons join and bbox /
  source / person_id round-trip cleanly.
- unassigned: person_name is None (not stale, not omitted), person_id
  is None.

These would have caught the prior regression — when the handlers
returned a bare FaceDetectionRow, person_name was structurally absent
from the response shape. A test that asserts person_name is populated
when person_id is set forces the join (or any equivalent) to exist.

A dangling-person_id case isn't covered: the FK on face_detections
makes that state structurally impossible at rest (ON DELETE SET NULL
zeroes the column when a person is removed), so there's nothing to
defend against.
2026-04-29 23:41:52 +00:00
Cameron Cordes
0c2f421a1f faces: PATCH/POST /image/faces returns person_name with the row
Both create_face_handler and update_face_handler returned the bare
FaceDetectionRow, so PATCH /image/faces/{id} (used by both bbox edits
and person assignment) replied without person_name. The carousel
overlay does an optimistic replace on this row — replacing the joined
FaceWithPerson with a row that has person_name = undefined visibly
dropped the VFD label off the bbox after every save.

Add a small hydrate_face_with_person helper that does the persons
lookup and assembles a FaceWithPerson, used by both handlers. The
list endpoint already does the join, so the PATCH/POST shape now
matches it.
2026-04-29 23:38:24 +00:00
Cameron Cordes
43cb60d3ad faces: re-embed on bbox edit instead of leaving the embedding stale
Phase 2 stored the new bbox on PATCH /image/faces/{id} but logged
"embedding now stale (Phase 3 will re-embed)" and moved on. That left
the embedding column pointing at the *old* face area while the bbox
described a new one — auto-bind cosine similarity and the cluster
suggester would silently rank the row as "the same face it was before
the edit" forever after, even though the geometry no longer matched.

Now: when the PATCH includes a bbox, the handler:
  1. Looks up the row to find its photo (library_id + rel_path).
  2. Crops the new bbox region with the same crop_image_to_bbox helper
     manual-create uses (10% pad on each side so the detector has
     ear/jaw context).
  3. POSTs the crop to face_client.embed for a fresh ArcFace vector.
  4. Stores both the new bbox AND the new embedding in one
     update_face transaction.

Errors map cleanly:
  - face_client disabled → 503 (bbox edit needs Apollo).
  - decode failure / no face in crop → 422.
  - Apollo CUDA OOM / unavailable → 503 transient.
  - Underlying row missing → 404.

About 100-500ms per edit on CPU, dominated by Apollo's inference call.
Acceptable for a manual operator action; the alternative (stale
embedding) silently broke the rest of the face stack.

Prerequisite for the upcoming carousel-side draw/resize bbox UI —
without re-embed, every operator-driven bbox tweak would corrode the
clustering/auto-bind quality. ApiPatchFaceBody on Apollo's side
already passes bbox through verbatim, so no Apollo change needed.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 23:10:25 +00:00
Cameron Cordes
7303fb8aa3 faces: ignore/junk bucket — DB schema + lazy-create endpoint
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>
2026-04-29 22:48:16 +00:00
Cameron Cordes
0e160f5d22 faces: include bbox on /faces/embeddings response
Apollo's cluster suggester wants to render a *face*-cropped thumbnail
for each cluster's representative — a multi-person photo with the
cluster about 'one' of them was unreadable when the thumb showed the
whole image. Plumbing bbox through means the UI can crop to the rep
face without an extra round-trip per cluster.

FaceEmbeddingRow gains bbox_x/y/w/h (Optional<f32>, mirrors the column
nullability — for status='detected' rows the CHECK constraint
guarantees they're populated, but the type stays nullable as
documentation). list_embeddings already loaded these from the
underlying FaceDetectionRow; this commit just stops dropping them
when constructing the response.

No DB changes; no behavior change for existing callers (the new
fields are additive).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 21:01:58 +00:00
Cameron Cordes
a24fac5511 faces: backfill missing content_hash from the file watcher
Photos indexed before content-hashing landed (or where the hash compute
failed silently on insert) end up in image_exif with NULL content_hash.
build_face_candidates keys on content_hash, so those rows would never
become face candidates without backfill — symptom: face detection logs
nothing despite photos being in the library and the watcher running.

The dedicated `backfill_hashes` binary already handles this; this
commit lets the watcher self-heal during full scans so the deploy
'just works' for face recognition without operator action.

Idempotent — subsequent scans see populated hashes and no-op. Bounded
per tick by FACE_HASH_BACKFILL_MAX_PER_TICK (default 500) so a watcher
tick on a 50k-photo legacy library doesn't blake3 every file in one
shot. For very large backlogs the dedicated binary is still faster
(no DAO mutex contention with the watcher loop).

Only runs when face_client.is_enabled(), so legacy deploys without
APOLLO_FACE_API_BASE_URL keep the same behavior.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 20:41:08 +00:00
Cameron Cordes
23f4941471 faces: surface enabled/disabled state + per-tick candidate count
Manual deploy debugging: 'Saved thumbnail' logs were visible (boot-time
thumbnail backfill) but no face_watch logs were appearing, with no
obvious way to tell whether the integration was disabled, hadn't reached
a full scan yet, or had simply seen no new files.

Two log lines:
  - watch_files startup: 'Face detection: ENABLED' / 'DISABLED (set
    APOLLO_FACE_API_BASE_URL or APOLLO_API_BASE_URL to enable)' so
    you can tell at a glance whether the env wired through.
  - process_new_files (debug-level): 'face_watch: scan tick — N image
    file(s) walked, M candidate(s) (library 'main', modified_since=...)'
    so an empty-candidate scan is distinguishable from a misconfigured
    or skipped one without bumping log level for the rest of the
    watcher.

No behavior change.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 20:19:17 +00:00
Cameron Cordes
41f93d70d1 faces: tighten bootstrap candidate filter, bump to 1.1.0
Filter <3-char tags and emoji/symbol-bearing tags out of the bootstrap
candidate list before grouping. Manual testing surfaced these as noise
the operator never tickets — they pushed real candidates lower in the
list and made the UI harder to scan. This is a hard filter (drop from
candidates entirely), not a heuristic flag — looks_like_person still
governs the default-checked decision for the rows that *do* survive.

is_plausible_name_token rules:
  - >= 3 chars after trimming (rejects "AB", "OK", whitespace-only)
  - Each char is alphabetic (any script — covers Renée, José, 田中太郎),
    whitespace, name-punctuation (' - . _ U+2019), or ASCII digit
  - Anything else (emoji, symbols, math, arrows, control codes) drops
    the whole tag

Digits stay allowed at this layer; looks_like_person handles "Trip 2018"
on the heuristic side. Lets a "Sarah2" alias still appear so the
operator can spot and confirm it manually, just unticked by default.

Cargo version bump 1.0.0 → 1.1.0 marks the face-recog feature surface
landing — Phase 2's schema + endpoints, Phase 3's file-watch hook, and
Phase 4's bootstrap + auto-bind are all behind APOLLO_FACE_API_BASE_URL,
so legacy 1.0 deploys without that env see no behavior change.

Tests: 1 new (faces::tests::is_plausible_name_token_filters_short_and_emoji)
covers the accept-list (Latin/accented/Asian scripts, hyphenated and
apostrophe names) and the reject-list (length floor, emoji classes,
symbols, leading/trailing whitespace handling).

cargo test --lib: 180 / 0; fmt + clippy clean.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 19:05:04 +00:00
Cameron Cordes
1859399759 faces: phase 4 — people-tag bootstrap + auto-bind on detection
Wires the existing string people-tags into the new persons table and
auto-binds new detections to a same-named person when the photo carries
exactly one matching tag. ImageApi has no notion of which tags are
people-tags today (purely a user mental model), so this is operator-
confirmed: the suggester surfaces candidates with a heuristic flag, the
operator confirms, then bootstrap creates persons rows. Auto-bind
follows on every detection thereafter.

New endpoints:
  GET  /tags/people-bootstrap-candidates
       Per case-insensitive name group: display name (most-frequent
       capitalization), normalized lowercase, summed usage_count,
       looks_like_person heuristic flag, already_exists check against
       the persons table. Sorted persons-likely-first then by count.
  POST /persons/bootstrap
       Body: {names: [string]}. Idempotent — pre-fetches the existing-
       name set so a duplicate request reports per-row "already exists"
       instead of 409-ing each insert. Created rows get
       created_from_tag=true; failed rows surface in `skipped` with a
       reason.

looks_like_person heuristic — conservative on purpose because the
operator confirms in the UI:
  - 1–2 whitespace-separated words
  - Each word starts uppercase, no digits anywhere
  - Single-word names not on a small denylist (cat, christmas, beach,
    sunset, untagged, ...). Two-word names skip the denylist so
    "Sarah Smith" is never false-rejected.

FaceDao additions:
  - find_persons_by_names_ci — bulk lowercase-name → person_id lookup
    via sql_query (Diesel's BoxedSelectStatement + LOWER() doesn't
    play well with the type system).
  - person_reference_embedding — L2-normalized mean of a person's
    detected embeddings, *filtered by model_version* so a future
    buffalo_xl row can never contaminate an in-flight buffalo_l auto-
    bind decision. Returns None when the person has no faces yet.
  - assign_face_to_person — sets face_detections.person_id and, only
    when persons.cover_face_id is NULL, claims this face as cover. The
    UI's hand-picked cover survives later auto-binds.
  - decode_embedding_bytes / cosine_similarity helpers — pub(crate)
    so face_watch can decode the wire bytes once and feed them through
    the cosine threshold.

Auto-bind in face_watch::process_one:
  After every successful detect, for each newly-stored auto face we
  pull the photo's tags, look up which (if any) map to existing
  persons, and:
    - skip when zero or multiple distinct persons are matched
      (multi-match is genuinely ambiguous; cluster suggester handles it)
    - on first face for a person: bind unconditionally so bootstrap can
      ever produce a usable reference
    - thereafter: bind iff cosine(new_emb, person_ref) >=
      FACE_AUTOBIND_MIN_COS (default 0.4, env-tunable to 0..=1)
  The reference embedding comes from person_reference_embedding under
  the same model_version as the candidate, so a model upgrade never
  silently re-anchors a person's centroid.

Plumbing: watch_files now constructs its own SqliteTagDao alongside the
other watcher DAOs and threads it through process_new_files →
run_face_detection_pass → process_one. The handler-side TagDao
registration in main.rs already covers bootstrap_candidates_handler;
no extra app_data wiring needed.

Tests: 8 new (faces.rs):
  - looks_like_person accepts/rejects/two-word-skips-denylist (3)
  - cosine_similarity on identical / orthogonal / opposite / mismatch /
    zero / empty inputs
  - decode_embedding_bytes round-trip + size validation
  - find_persons_by_names_ci groups case + handles empty input
  - person_reference_embedding filters by model_version (buffalo_l ref
    must not include buffalo_xl rows)
  - assign_face_to_person sets cover when unset, doesn't overwrite

cargo test --lib: 179 / 0; fmt + clippy clean for new code.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 18:55:01 +00:00
Cameron Cordes
f985a0d658 faces: surface UNIQUE constraint as 409, not 500
Manual smoke test caught a bug: POST /persons with a duplicate name
returned 500 with the body 'insert person Cameron' instead of the
intended 409 Conflict.

Root cause: the handler keyed on `format!("{}", e).contains("unique")`,
but anyhow's plain Display only renders the *outermost* context
("insert person Cameron") and hides the diesel error nested below
('UNIQUE constraint failed: persons.name'). The string check was a
false negative on every duplicate.

Fix: walk the source chain and downcast for
diesel::result::Error::DatabaseError(UniqueViolation, _) — exposed
via a shared `is_unique_violation` helper used by both
create_person_handler and update_person_handler. Error bodies for
non-unique failures now use `{:#}` so the body actually carries the
underlying cause when the user surfaces it.

merge_persons_handler also moves to `{:#}` for richer error bodies;
the "itself" check was already structural and unaffected.

Regression test (faces::tests::is_unique_violation_walks_chain) pins
both the bug shape ({} doesn't surface UNIQUE) and the fix
(is_unique_violation correctly downcasts the chain), so a future
refactor of error handling can't silently re-bury this.

cargo test --lib: 171 / 0; fmt + clippy clean.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 18:44:10 +00:00
Cameron Cordes
4dee7b6f73 faces: phase 3 — file-watch hook drives auto detection
Wire face detection into ImageApi's existing scan loop so new uploads
pick up faces automatically and the initial backlog grinds through on
full-scan ticks. No new job system; Phase 2's already_scanned check
makes the work implicitly idempotent (one face_detections row per
content_hash, including no_faces / failed marker rows).

face_watch.rs (new):
  - run_face_detection_pass(library, excluded_dirs, face_client,
    face_dao, candidates) — sync entry point. Builds a per-pass tokio
    runtime and fans out detect calls bounded by FACE_DETECT_CONCURRENCY
    (default 8). The watcher thread itself stays sync.
  - filter_excluded — applies the same PathExcluder /memories uses, so
    @eaDir / .thumbnails / EXCLUDED_DIRS-listed paths skip detection
    before we burn a detect call (and Apollo's GPU memory) on junk.
  - read_image_bytes_for_detect — RAW/HEIC route through
    extract_embedded_jpeg_preview because opencv-python-headless can't
    decode either; everything else gets a plain std::fs::read so EXIF
    orientation reaches Apollo's exif_transpose intact.
  - process_one — translates Apollo's response into the Phase 2 marker
    contract: faces[] empty → no_faces; FaceDetectError::Permanent →
    failed (don't retry); Transient → no marker (next scan retries);
    success with N faces → N detected rows with the embeddings unpacked.

main.rs (process_new_files + watch_files):
  - watch_files now also takes face_client + excluded_dirs; the watcher
    thread builds a SqliteFaceDao the same way it builds ExifDao /
    PreviewDao.
  - After the EXIF write loop, build_face_candidates queries image_exif
    for the just-walked image paths' content_hashes (covers new uploads
    and pre-existing backlog), filters out anything already_scanned, and
    hands the rest to face_watch::run_face_detection_pass.
  - Bypassed wholesale when face_client.is_enabled() is false — keeps
    the watcher usable on legacy deploys where Apollo isn't configured.

Tests: 5 face_watch unit tests cover the parts that don't need a real
Apollo:
  - filter_excluded drops dir-component patterns (@eaDir) without
    matching substring file names (eaDir-not-a-thing.jpg keeps).
  - filter_excluded drops absolute-under-base subtrees (/private).
  - empty EXCLUDED_DIRS short-circuits cleanly.
  - read_image_bytes_for_detect passes JPEG bytes through verbatim
    (orientation must reach Apollo unmodified).
  - read_image_bytes_for_detect falls through to plain read when a
    RAW-extension file has no embedded preview, so Apollo gets a chance
    to 422 and we mark failed rather than infinitely-retrying.

cargo test --lib: 170 / 0; fmt and clippy clean for new code.
End-to-end (drop a photo → face_detections row appears) needs Apollo
running and is deferred to deploy-time verification.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 18:21:19 +00:00
Cameron Cordes
f77e44b34d faces: fix PathExcluder false-positive + cover face_client/crop in tests
PathExcluder was iterating every component of the absolute path,
including the system prefix. Two of the existing memories tests had
been failing on master because tempdir() lives under /tmp on Linux
and a pattern like "tmp" then matched the system /tmp component
rather than anything the user actually asked to exclude. Phase 3's
file-watch hook will use the same code to skip @eaDir / .thumbnails
under each library's BASE_PATH, so the bug would hide every photo
on a host whose BASE_PATH passes through a directory named the same
as a user pattern.

Fix: store base in PathExcluder and strip it before scanning
components. A path that lives outside base falls through to the
no-match branch (defensive — nothing legit hits that today).

Also extracted the face_client error classification into a pure
classify_error_response(status, body) so the marker-row contract
with Apollo (422 → Permanent / 'failed', 5xx → Transient / defer)
is unit-testable without spinning up an HTTP server.

New tests:
  memories::tests::test_path_excluder_*           — 2 previously
    failing tests now pass.
  ai::face_client::tests::classify_*              — 4 cases:
    422 decode_failed → Permanent, 503 cuda_oom → Transient
    (handles both string and {code:..} detail shapes), 5xx →
    Transient + other 4xx → Permanent, unparseable HTML body still
    classifies on status.
  faces::tests::crop_*                            — 3 cases:
    invalid bbox rejected, valid bbox round-trips through JPEG
    decode, corner crop with 10% padding clamps inside source.

cargo test --lib: 165 passed / 0 failed (was 156 / 2 failed).
cargo fmt and clippy on new code clean. The remaining
sort_by clippy warnings in pre-existing files (memories.rs,
files.rs, exif.rs) are unrelated and present on master.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 18:09:44 +00:00
Cameron Cordes
860169032b 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>
2026-04-29 18:03:42 +00:00
6642db3c8b Merge pull request 'feat/apollo-places-tool and Geo Tagging Exif' (#60) from feat/apollo-places-tool into master
Reviewed-on: #60
2026-04-28 23:09:33 +00:00
Cameron Cordes
57fb0bcd3c EXIF GPS write: POST /image/exif/gps via exiftool
New endpoint accepts {path, library, latitude, longitude} and shells
out to exiftool to write GPSLatitude/GPSLongitude (with N/S, E/W refs)
into the file's EXIF in place. After the write, the handler
re-extracts EXIF and updates the image_exif row so the DB stays in
sync — the response carries the updated metadata block in one
round-trip. Falls through to store_exif if the row is missing.

`exif::write_gps` is the small helper. `-overwrite_original` so no
.orig sidecar is left behind. Validates lat/lon range + supports_exif
before spawning exiftool. Format support matches the existing read
path (JPEG / TIFF / RAW / HEIF / PNG / WebP) — videos still need a
different writer and aren't covered.

Apollo's "+ PIN" carousel button (separate commit on the Apollo side)
calls this through /api/photos/exif/gps. Drive-by: cargo fmt one-line
collapse on apollo_client.rs.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-28 22:25:40 +00:00
Cameron Cordes
4ae7be35e9 Apollo Places: enrich insights with personal place name + notes
Optional integration with the sibling Apollo project's user-defined
Places (name + lat/lon + radius_m + description + category). When
APOLLO_API_BASE_URL is set, the per-photo location resolver folds the
most-specific containing Place into the LLM prompt's location string —
"Home (My house in Cambridge) — near Cambridge, MA" rather than the
city name alone. Smallest-radius wins; Apollo sorts server-side via
/api/places/contains, so the carousel badge in Apollo and the prompt
string here always agree.

Adds an agentic tool `get_personal_place_at(latitude, longitude)` that
the LLM can call during chat continuation. Tool description tells the
model the call returns the user's free-text notes, not just a name.
Deliberately narrow — no enumerate-all variant, lat/lon required.

Unset APOLLO_API_BASE_URL = legacy Nominatim-only path, tool is not
registered. 5 s timeout; all errors degrade silently.

Tests: 5 unit tests for compose_location_string (Apollo only, Nominatim
only, both, both-with-description, neither).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-28 19:11:12 +00:00
9d58547ce3 Merge pull request 'feat/raw-thumb-embedded-preview' (#59) from feat/raw-thumb-embedded-preview into master
Reviewed-on: #59
2026-04-28 17:21:27 +00:00
Cameron Cordes
6521a328bf RAW preview: exiftool fallback for MakerNote / SubIFD previews
kamadak-exif's In::PRIMARY / In::THUMBNAIL only address IFD0 and IFD1.
On modern Nikon NEFs the full-res review JPEG lives in the MakerNote's
PreviewIFD (and many Canon CR2s / DNGs put theirs in a SubIFD chain) —
both unreachable through the existing reader, so the previous patch
still produced no preview for those files and the pipeline fell through
to ffmpeg, which writes black frames when it can't decode the RAW.

Add a slow-path layer in extract_embedded_jpeg_preview that shells out
to exiftool for PreviewImage / JpgFromRaw / OtherImage (one process per
tag). All candidates from both layers are pooled and the largest valid
JPEG wins. exiftool not on PATH degrades to fast-path-only behavior
rather than breaking — the fallback is a strict superset.

Documented the new optional dependency in README.md and CLAUDE.md with
install commands for apt / brew / winget / choco.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-28 17:13:36 +00:00
Cameron Cordes
00b3c80141 RAW: try IFD0 + IFD1 for embedded preview, serve at full size
The thumbnail pipeline's embedded-JPEG extractor only checked IFD1
(THUMBNAIL), which on many Nikon NEFs is missing or zero-length even
when IFD0 (PRIMARY) carries a perfectly good 1-2 MP reduced-resolution
preview the camera writes for in-body review. The previous behavior
produced black thumbs on disk: the buggy IFD1 pointer resolved to a
short byte sequence that happened to satisfy the SOI sanity check,
image::load_from_memory accepted it, and the resize path quietly wrote
a black JPEG.

Now both IFDs are checked and the larger valid JPEG wins. Format-
agnostic: applies to every TIFF-based RAW (NEF / ARW / CR2 / DNG / RAF /
ORF / RW2 / PEF / SRW / TIFF). is_tiff_raw is now pub so main.rs can
gate its full-size handler on it.

Also extends the /image handler so size=full requests for RAW formats
serve the embedded preview as image/jpeg instead of NamedFile-streaming
the original RAW bytes - browsers can't decode a .nef container, so
<img src=...> would otherwise land as a broken image. Falls through to
NamedFile if no preview is present, preserving the historical behavior
for callers that genuinely want the original bytes.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-28 16:52:10 +00:00
a53c3ae514 Merge pull request 'feature/exif-batch-endpoint for Apollo' (#58) from feature/exif-batch-endpoint into master
Reviewed-on: #58
2026-04-28 12:58:30 +00:00
Cameron Cordes
7621282419 Thumb orientation + library filter on /photos/exif
Two follow-ups on the same feature branch:

1. Bake EXIF orientation into generated thumbnails. The `image` crate
   doesn't apply Orientation on load, and `save_with_format(..Jpeg)`
   drops EXIF — so portrait phone shots ended up sideways in any client
   that displays the cached thumb directly (no EXIF tag for the browser
   to compensate from). New `exif::read_orientation` reads the tag
   cheaply (no full EXIF parse) and `exif::apply_orientation` does the
   rotate/flip via image's existing `rotate90/180/270` + `fliph/flipv`.
   Applied in both branches of `generate_image_thumbnail` (RAW embedded-
   JPEG path and the regular `image::open` path). Existing thumbnails
   in the cache are still wrong-orientation; wipe the thumb dir or run
   a one-off backfill once this lands.

2. Optional `library` query param on `/photos/exif`. Accepts numeric id
   or name (same shape as `/image?library=...`), resolved via the
   existing `resolve_library_param` helper so a bad value 400s before
   we touch the DAO. Filter is applied post-query in the handler
   rather than pushed into `query_by_exif` to keep the DAO trait
   (and its test mocks) unchanged. Cheap enough at typical library
   counts; can be moved into SQL later if it ever isn't.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-27 17:29:36 -04:00
Cameron Cordes
c6f82ebaba Batch EXIF endpoint: GET /photos/exif
Adds a single round-trip projection of `image_exif` for every photo whose
`date_taken` falls in `[date_from, date_to]`. Wraps the existing
`ExifDao::query_by_exif` DAO method which already handles the SQL filter
in one query against the covering index — the only missing piece was
HTTP plumbing.

Designed for window-scoped consumers like Apollo's photo-to-track
matcher, which currently does N+1 (one `/photos` listing + one
`/image/metadata` per photo). Because `/image/metadata` serializes on
`Data<Mutex<dyn ExifDao>>`, that pattern can take 10s+ for windows with
hundreds of photos. The new endpoint takes one mutex acquisition for
the whole batch.

Response shape:
  { photos: [
      { file_path, library_id, library_name,
        camera_model, width, height,
        gps_latitude, gps_longitude, date_taken } ],
    total: N }

Two notes on scope:
- Photos with NULL `date_taken` are excluded by `query_by_exif`'s
  semantics. Filename-extracted dates are not synthesized here; rare
  callers that need that fallback can still hit `/image/metadata`.
- GPS columns are stored as f32 in image_exif to keep row size small;
  the JSON shape widens to f64 so clients don't have to know about the
  on-disk precision.

Library names are pre-mapped from `app_state.libraries` once and
stamped on each row, avoiding an O(rows × libraries) linear scan.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-27 16:38:53 -04:00
9cf3af383d Merge pull request '006-bin-cleanup-and-progress' (#57) from 006-bin-cleanup-and-progress into master
Reviewed-on: #57
2026-04-27 20:28:32 +00:00
Cameron
b9d5578653 feat(bins): multi-library populate_knowledge + progress UX
populate_knowledge now loads real libraries from the DB instead of
fabricating a single library_id=1 row from BASE_PATH. Adds --library
<id|name> to restrict the walk and validates --path against the selected
library roots. The full library set is still passed to InsightGenerator so
resolve_full_path can probe every root when an insight resolves to a
different library than the one being walked.

Adds indicatif progress bars across the long-running utility binaries via
a shared src/bin_progress.rs helper (determinate bar + open-ended spinner
with consistent styling). Per-batch info! noise is replaced by the bar's
throughput/ETA; warnings and errors route through pb.println so they
scroll above the bar instead of fighting with it.

  populate_knowledge   spinner during scan, determinate bar over all libs
  backfill_hashes      spinner with running hashed/missing/errors counts
  import_calendar      determinate bar; embedding/store failures inline
  import_location_*    determinate bar advancing by chunk size
  import_search_*      determinate bar; pb cloned into the spawn task
  cleanup_files P1     determinate bar over DB paths
  cleanup_files P2     determinate bar; pb.suspend() around y/n/a/s prompt

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 23:55:33 -04:00
Cameron
d5f944c7b6 chore(bins): retire unused migrate_exif
Single-library hardcoded (library_id=1) and missing content_hash/size_bytes
backfill, so the watcher's full-scan path subsumes everything it does.
Removed the binary and its CLAUDE.md reference.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 23:55:06 -04:00
2db611e1c1 Merge pull request 'OpenRouter Support, Insight Chat and User injection' (#56) from 005-llm-client-trait into master
Reviewed-on: #56
2026-04-26 23:01:33 +00:00
Cameron
21e624da6b fix(video): sentinel for failed HLS encodes to stop retry loop
Previously a corrupt source (e.g. truncated mp4 with no moov atom) would be
re-queued on every directory scan: cleanup_partial_hls wipes the temp
playlist on ffmpeg failure, leaving no .m3u8 to short-circuit the next pass.

Mirrors the thumbnail .unsupported sentinel pattern: on ffmpeg failure,
write <playlist>.m3u8.unsupported, and treat its presence as "done" in both
the ScanDirectoryMessage filter and the QueueVideosMessage check. Delete
the sentinel to force a retry.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 01:06:13 -04:00
Cameron
021d1bffc0 chore: ignore db backups and local .idea config files
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 19:13:28 -04:00
Cameron
fa21b0d73d chore(ai): disable default few-shot insight ids
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 19:12:25 -04:00
Cameron
0e55a6b125 fix(ai): treat rewind at end of history as no-op success
The mobile client's regenerate-after-failure flow sends a discard index
equal to the server's rendered count (its optimistic user bubble for the
failed turn was never persisted). find_raw_cut treated this as out of
range, surfacing as "Chat rewind failed: discard_from_rendered_index out
of range" and blocking the retry.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 19:12:17 -04:00
Cameron
0ebc2e9003 feat(ai): rerank timing + think:false + OpenRouter error detail
- search_rag reranker now logs wall-clock time around the ollama.generate
  call, the candidate count / top-N going in, and the final reordering.
  The "final indices" + swap-count line is info level so it's always
  visible; detailed before/after previews stay at debug for when you want
  to inspect reranker quality.
- New OllamaClient::generate_no_think convenience that sets Ollama's
  top-level think:false on the request, plumbed through try_generate via
  a new internal generate_with_options. Used only by the reranker today;
  avoids the chain-of-thought tax on reasoning models (Qwen3/VL,
  DeepSeek-R1 distills, GPT-OSS) when the task has nothing to reason
  about. Server-side no-op on non-reasoning models.
- OpenRouter chat_with_tools "missing choices[0]" error now includes the
  actual response body — extracts structured {error: {code, message}}
  when OpenRouter surfaces it (common for upstream-provider issues like
  rate limits and content moderation), otherwise falls back to a
  truncated raw-JSON view.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 16:19:45 -04:00
Cameron
e5781325c6 fix(ai): render tool-call arguments as compact JSON in logs
Switch the "Agentic tool call" log from {:?} (Debug) to {} (Display) on
serde_json::Value. Display produces compact JSON — `{"date":"2023-08-15"}`
instead of `Object {"date": String("2023-08-15")}` — which is what the
model actually sent and what a human reading the log wants to see.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 14:25:53 -04:00
Cameron
d43f5fc991 docs: document OLLAMA_REQUEST_TIMEOUT_SECONDS env var
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 13:54:23 -04:00
Cameron
f0ae9f95dc feat(ai): few-shot exemplars + sticky Ollama preference
- 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>
2026-04-24 13:54:06 -04:00
Cameron
29f32b9d22 FFMPEG playlist improvements
Better playlist management, .tmp renaming, HLS playlist parameter and concurrency tweaking.
2026-04-24 10:08:03 -04:00
Cameron
13b9d54861 fix(scan): quiet startup scans & thumbnail RAW/HEIC
Three recurring issues on every full scan:

1. Video playlist scans re-enqueued every file only to reject it as
   AlreadyExists. Pre-filter in ScanDirectoryMessage and QueueVideosMessage
   so we skip videos whose .m3u8 already exists, and demote the leaked
   AlreadyExists log to debug.

2. image crate was built with only jpeg/png features, so webp/tiff/avif
   files logged "format not supported" every scan. Enable those features.

3. RAW (ARW/NEF/CR2/...) and HEIC thumbnails weren't generated, so the
   scan kept retrying them. Try the file's embedded JPEG preview via
   kamadak-exif first (fast, pure-Rust, works on Sony ARW where ffmpeg's
   TIFF decoder fails). Fall back to ffmpeg for HEIC/HEIF and RAWs with
   no preview. Anything still undecodable gets a <thumb>.unsupported
   sentinel so future scans skip it.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-23 20:47:13 -04:00
Cameron
dc2a96162e fix(dates): prefer earliest of fs created/modified as fallback
On copied or restored files (e.g. a backup library), the OS stamps
created at copy time while modified is preserved from the source, so
the earlier of the two is a better proxy for when the content
originated. Adds utils::earliest_fs_time and threads it through the
three spots that fall back to filesystem dates: photos-list sort,
memories grouping, and insight-generation timestamp.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-23 17:20:12 -04:00
Cameron
d54419e779 style: cargo fmt drift
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-23 17:19:59 -04:00
Cameron
aa651d1c7b feat(ai): iteration budget in prompt + preserve photo-knowledge links
- Inject the max-iterations budget into the agentic system prompt for
  both insight generation and chat turns. Chat does this per-turn by
  appending a note to the replayed system message and restoring it
  before persistence so the note doesn't accumulate across turns.
- Stop deleting entity_photo_links at the start of agentic insight
  generation. The clear made recall_facts_for_photo always return
  empty, wasting a tool call and discarding knowledge from prior runs.
  Re-linking the same entity is already an INSERT OR IGNORE no-op.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-23 16:28:48 -04:00
Cameron
6831f50993 feat(ai): USER_NAME env + shared summary prompt + test-bin knobs
Introduces USER_NAME (default "Me") as the single source for the message
sender label and the first-person persona across daily summaries, SMS
context, insight generation, and chat. Eliminates the "Me:" transcript /
"what I did" ambiguity that confused smaller models, and unhardcodes
"Cameron" from prompt text + the knowledge-graph owner entity. Set
USER_NAME=Cameron in .env to preserve the existing owner entity row
(keyed on UNIQUE(name, entity_type)) — otherwise the next run creates
a fresh owner entity and orphans the existing facts/photo-links.

Also:
- search_messages redirect: when the model calls it with date/contact
  but no query, return a hint pointing at get_sms_messages instead of
  a bare missing-parameter error (prevents same-turn retry loops)
- sharpen search_messages vs get_sms_messages tool descriptions so
  content-vs-time-based intent is unambiguous
- extract build_daily_summary_prompt (+ DAILY_SUMMARY_MESSAGE_LIMIT,
  DAILY_SUMMARY_SYSTEM_PROMPT) shared by daily_summary_job and
  test_daily_summary binary — prompt tweaks now land in both
- EMBEDDING_MODEL const; fixes both insert sites that stored
  "mxbai-embed-large:335m" while generate_embeddings actually runs
  "nomic-embed-text:v1.5"
- test_daily_summary: add --num-ctx / --temperature / --top-p /
  --top-k / --min-p flags wired into OllamaClient setters, and print
  the configured knobs at the top of each run
- OllamaClient::generate now logs prompt/gen token counts and tok/s
  via log_chat_metrics (symmetric with chat_with_tools)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-22 23:39:37 -04:00
Cameron
e4a3536f87 feat(ai): search_messages tool + RAG reranker
Adds a search_messages tool that hits the Django FTS5/semantic/hybrid
endpoint for keyword-quality text search over message bodies, and an
LLM-based reranker inside tool_search_rag (gated by SEARCH_RAG_RERANK,
default on). Reranker pulls ~3x candidates from the vector index, asks
the chat model to rank by relevance, and falls back to vector order on
parse failure.

The reranker shares the active chat turn's OllamaClient so num_ctx and
sampling match — otherwise Ollama unloads/reloads the model on every
rerank call. (Unverified end-to-end; caught by inspection, awaiting
e2e confirmation.)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-22 10:56:03 -04:00
Cameron
e51cd564a3 docs: chat continuation endpoints + env vars
Document the four new chat endpoints, SSE event shape, backend
routing rules, rewind semantics, amend mode, and the
AGENTIC_CHAT_MAX_ITERATIONS cap.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 17:32:43 -04:00
Cameron
079cd4c5b9 feat(ai): streaming chat endpoint with live tool events
Add LlmClient::chat_with_tools_stream and SSE endpoint
POST /insights/chat/stream that emits text deltas, tool_call /
tool_result pairs, truncated notice, and a terminal done frame as the
agentic loop runs.

- Ollama: parses NDJSON from /api/chat stream, accumulates content
  deltas, emits Done with tool_calls from the final chunk.
- OpenRouter: parses OpenAI-compatible SSE, reassembles tool_call
  argument deltas by index, asks for stream_options.include_usage.
- InsightChatService spawns the loop on a tokio task, feeds events
  through an mpsc channel, persists training_messages at the end.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 16:57:41 -04:00
Cameron
c2bd3c08e1 feat(ai): surface tool invocations in chat history
load_history now groups preceding tool_call + tool_result scaffolding
under each assistant reply as `tools: [{name, arguments, result}]`.
Result bodies over 2000 chars are truncated for payload size with a
`result_truncated` flag; the full value remains in training_messages.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 16:03:53 -04:00
Cameron
65ab10e9a8 feat(ai): chat rewind + ollama metrics logging
Rewind: POST /insights/chat/rewind truncates training_messages at a
given rendered index, dropping the target message plus any preceding
tool-call scaffolding. The initial user prompt is protected.

Metrics: log prompt_eval_count/duration and eval_count/duration from
every Ollama chat response, rendered as tokens + ms + tok/s.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 15:16:32 -04:00
Cameron
0b9528f61e feat(ai): chat continuation for photo insights (server v1)
Adds POST /insights/chat and GET /insights/chat/history. Replays the
stored agentic conversation through the same backend the insight was
generated with (or a per-turn override), runs a short tool-calling
loop, and persists the extended history in append or amend mode.

Backend switching: same-backend or hybrid->local replay verbatim;
local->hybrid is rejected in v1 (would require on-the-fly vision
description rewrite).

Per-(library, file) async mutex serialises concurrent turns. Soft
context budget drops oldest tool_call+result pairs when the
serialized history exceeds num_ctx - 2048 tokens.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 13:00:27 -04:00
Cameron
e2eefbd156 feat(ai): curated OpenRouter model picker for hybrid backend
Add OPENROUTER_ALLOWED_MODELS env var and GET /insights/openrouter/models
endpoint returning the curated list verbatim. Drop the live capability
precheck in hybrid mode — trust the operator's allowlist; bad ids surface
as a chat-call error.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 10:36:19 -04:00
Cameron
3ac0cd62eb feat(ai): hybrid backend mode for agentic insights
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>
2026-04-20 22:30:40 -04:00
Cameron
e799ba716c feat(ai): add OpenRouterClient implementing LlmClient
OpenAI-compatible client for OpenRouter. Translates canonical wire shapes at
the boundary: tool-call arguments stringify on send / parse on receive
(accepting both string and native-object forms); images rewritten from the
base64 images field into content-parts with image_url entries; role=tool
messages inherit tool_call_id from the preceding assistant's tool calls.

/models parsed into ModelCapabilities via supported_parameters (tool use)
and architecture.input_modalities (vision). 15-minute capabilities cache.
Bearer auth; HTTP-Referer / X-Title attribution headers optional.

Not wired into request routing yet — first consumer arrives with hybrid
backend mode. 11 unit tests cover the translation helpers.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-20 22:18:29 -04:00
Cameron
0073409b3d refactor: introduce LlmClient trait (no-op)
Preparation for a second LLM backend (OpenRouter) and hybrid vision-local /
chat-remote mode. Shared wire types (ChatMessage, Tool, ToolCall, etc.) move
into a new src/ai/llm_client.rs and are re-exported from ollama.rs so
existing imports keep working. OllamaClient now implements LlmClient.

No behavior change; callers still hold the concrete OllamaClient. Caller
migration to Arc<dyn LlmClient> is deferred to the PR that wires hybrid
backend routing.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-20 22:11:05 -04:00
702aa8078c Merge pull request '004 Multi-library Support' (#54) from 004-multi-library into master
Reviewed-on: #54
2026-04-21 01:55:22 +00:00
Cameron
bffe604527 Remove potentially confusing TZ from insight generator 2026-04-21 01:55:07 +00:00
Cameron
39c212b0e6 Bump to 1.0.0 for multi-library support 2026-04-21 01:55:07 +00:00
Cameron
a35b45fd36 feat: expand insight tool result caps and render timestamps in local time
Doubled default row caps for search_rag/get_sms_messages/get_calendar_events/recall_entities and exposed an optional `limit` parameter on each so the agent can tune per call. Render all LLM-facing timestamps as server-local time with explicit offset so smaller models stop misreading UTC as wall-clock time.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
3027a3ffda perf: DB-backed recursive /photos + watcher reconciliation
Recursive listings now query image_exif instead of walking disk, taking
union-mode /photos from ~17s to sub-second on a 10k-file library. The
watcher's full scan prunes stale image_exif rows so the DB stays in
parity with the filesystem when files are deleted externally.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
4a775b5e9b test: cover resolve_library_param and per-library ExifDao filter
Adds 9 unit tests around the library plumbing:
- resolve_library_param branches (absent, empty/whitespace, numeric id,
  name, unknown id, unknown name)
- Library::resolve symmetry with strip_root
- ExifDao::get_all_with_date_taken in union and scoped modes

Introduces SqliteExifDao::from_connection test constructor mirroring the
existing preview_dao pattern so DAO tests can drive an in-memory SQLite.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
b04dd8b601 fix: demote path-not-exists validation errors to debug
The /image cross-library fallback tries the resolved library first and falls
back to any library holding the rel_path. The first attempt emitted error-level
noise on every grid tile in union mode. Split the validation error so only
traversal attempts log at error; missing-file cases log at debug.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
2c8de8dcc6 feat: union /photos and /memories across libraries
When `library` is omitted, both endpoints now walk every configured
library root, interleave the results, and tag each row with its source
library via the parallel `photo_libraries` / per-row `library_id`
arrays. Previously the handlers fell back to the primary library,
silently hiding the rest.

Threads a parallel `file_libraries: Vec<i32>` through the sort/paginate
helpers so library attribution survives sorting and pagination.
Directory names are de-duplicated across libraries.

`get_all_with_date_taken` grows an optional library filter so memories
can scope its EXIF query per-library during the union walk.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
586b735af5 feat: include per-photo library id in /photos response
Adds a parallel `photo_libraries: Vec<i32>` array alongside `photos`
in `PhotosResponse` so clients can render per-thumbnail badges.
Populated with the scoped library id at the two main return sites;
left empty for `/favorites` since favorites are library-agnostic.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
c2ee3996be chore: apply cargo fmt + clippy cleanup across crate
Silence forward-looking dead_code on unused DAO modules, annotate
individual placeholder items, rewrite tautological assert!(true/false)
in token tests as panic! arms, and pick up fmt drift.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
a0f3bfab5f fix: validate gps-summary path against every library
The /photos/gps-summary handler validated the incoming path against
the primary library's root with new_file=false, which requires the
path to exist on disk. For a viewer opened on a file from a
non-primary library, tapping the GPS link produced activePath =
<folder from lib 2>, the primary-only check failed, and the server
400'd — so the map came up empty.

Validation here is purely a traversal guard (the DAO does a prefix
LIKE against rel_path), so we now accept the path as long as any
configured library can resolve it without escaping its root.

Also applies cargo fmt drift on files touched this session.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
54a1df60b8 fix: resolve preview clip rel_path against all libraries
PreviewClipGenerator stripped a single base_path, so videos in a
non-primary library ended up with the absolute path as 'relative'.
On Windows, PathBuf::from(preview_clips_dir).join(absolute) replaces
with the absolute path, and .with_extension("mp4") on a .mp4 input
yields the input path — ffmpeg then errors out with 'cannot edit
existing files in place'.

The generator now holds Vec<Library> and strips whichever root
actually contains the video, with separator normalization to match
the rest of the code.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
7becbc0737 fix: normalize rel_path separators in non-recursive /photos listing
On Windows, strip_prefix preserves backslashes, so the non-recursive
branch was looking up tags for 'Melissa\img1.jpg' while tagged_photo
stores 'Melissa/img1.jpg' — every file was filtered out. Normalize to
'/' to match the watcher and populate_knowledge.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
e6ee38edec fix: resolve media across libraries for video, metadata, and insights
The /video/generate and /image/metadata handlers assumed files live under
the resolved library only, which broke when a mobile client passed no
library (union mode) but the file lived in a non-primary library. Both
now fall back to scanning every configured library for an existing file.

InsightGenerator held a single base_path, so vision-model loads and
filename-date fallbacks failed for non-primary libraries. It now takes
Vec<Library> and probes each root in resolve_full_path.

/image/metadata responses now carry library_id/library_name so the
mobile viewer can surface which library a file belongs to.

Thumbnail generation at startup is now spawned on a background thread
so the HTTP server can accept traffic while large libraries backfill.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
2d942a9926 feat: content-hash-aware tag/insight sharing + library scoping
Tags and insights now follow content across libraries via content_hash
lookups on the read path, so the same file indexed at different rel_paths
in multiple libraries shares its annotations. Recursive tag search scopes
hits to the selected library by checking each tagged rel_path against
the library's disk (with a content-hash sibling fallback so tags attached
under one library's rel_path still match a content-equivalent file in
another). The /image and /image/metadata handlers fall back across
libraries when the file isn't under the resolved one, so union-mode
search results (which carry no library attribution in the response)
still serve correctly.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
c01a0479b7 fix: honor library param in /image, /photos, /memories
The Phase 3 plumbing accepted `library=` but didn't actually route
requests through the scoped library once it was resolved. Three
concrete bugs surfaced when testing against a second mounted library:

- `/image` always resolved paths against AppState.base_path (primary),
  so thumbnails for non-primary libraries 400'd when their rel_paths
  didn't exist under primary. Now resolves against the scoped library
  and defaults to primary when the param is omitted.

- `/memories` walked the scoped library correctly but its helper
  functions hardcoded `library_id: PRIMARY_LIBRARY_ID` on every
  MemoryItem, causing clients to route thumbnails back to primary
  regardless of which library the memory actually came from.

- `/photos` non-recursive listing delegated to a `RealFileSystem`
  constructed from AppState.base_path at startup, so walks always
  hit primary even when `library=2` was passed. The non-primary
  path now uses list_files against the scoped library's root;
  primary still goes through FileSystemAccess to preserve the
  existing test mock plumbing.

Also adds `library` to ThumbnailRequest so the /image query param
is actually parsed.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
0aaea91cc2 feat: add content_hash backfill + register every media file
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>
2026-04-21 01:55:07 +00:00
Cameron
ce5b337582 feat: make file watcher, thumbnails, and upload library-aware
`watch_files` and `create_thumbnails` now iterate every configured
library, tagging rows with the correct `library_id`. `process_new_files`
takes a `&Library` so InsertImageExif no longer hardcodes the primary
library. Upload accepts an optional `library` query param to pick a
target library; omitted still defaults to primary for backwards
compatibility.

Hash-keyed thumbnail/HLS storage with dual-lookup fallback is deferred
to Phase 5, where it's bundled with the content hash backfill that
actually makes the hash-keyed paths meaningful. Until hashes are
populated, the legacy mirrored layout is a no-op to change.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
48e5de6eab feat: add GET /libraries and library query param plumbing
New `/libraries` endpoint returns configured libraries so clients can
discover them. `FilesRequest` and `MemoriesRequest` gain an optional
`library` param (accepts name or numeric id). Unknown values are
rejected with 400; absent values span all libraries. `/memories`
now scopes its filesystem walk + EXIF query to the resolved library.
`MemoryItem` carries `library_id` so union-mode clients can render a
per-item source badge.

Behavior is unchanged in single-library mode: omitting `library` still
returns results from the primary library, which is the only one
configured until a second row is added to the libraries table.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-21 01:55:07 +00:00
Cameron
ffcddbb843 feat: multi-library foundation (schema + libraries module)
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>
2026-04-21 01:55:07 +00:00
2f4edba08c Merge pull request '003-knowledge-memory' (#55) from 003-knowledge-memory into master
Reviewed-on: #55
2026-04-21 01:54:34 +00:00
Cameron
8bc948b297 Insight prompt tweaks 2026-04-17 11:55:33 -04:00
Cameron
b7e1bdf1fd feat: add sampling param CLI flags to populate_knowledge binary
Adds --temperature, --top-p, --top-k, --min-p flags so batch runs can
tune the same sampling params now supported by the API endpoints.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-16 14:23:45 -04:00
Cameron
3059adfd37 Add missing DB migration sql for training data 2026-04-15 09:28:53 -04:00
Cameron
b599f7a34b feat: add temperature, top_p, top_k, min_p params to insight generation
Expose Ollama sampling params through the insight generation endpoints
so users can tune creativity/determinism per request. All four are
optional — omitted values fall through to the model's server-side
defaults.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-15 09:27:59 -04:00
Cameron
c703a47f17 Add the ability to rate insights to curate training data 2026-04-13 09:23:40 -04:00
Cameron
da16fddce3 Address path traversal and other security fixes 2026-04-10 14:58:57 -04:00
Cameron
e1c32b6584 Tweak Prompt 2026-04-10 14:30:31 -04:00
Cameron
65e938035f fix: reduce duplicate entities from weak model inconsistency
Adds normalize_entity_type() which lowercases and canonicalises synonyms
(location→place, human→person, etc.) before every upsert. The SQL lookup
now uses lower(entity_type) on both sides so existing dirty rows (Person,
Location) correctly deduplicate against normalised writes without a migration.

Adds a pre-flight similarity check in tool_store_entity: before upserting,
searches active entities of the same type using the first name token. Any
non-exact matches are appended to the tool response so the agentic loop
can choose to reuse an existing entity ID rather than create a duplicate.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-07 18:27:09 -04:00
Cameron
bc3b313e2e feat: add populate_knowledge batch binary with configurable timeout
Adds a standalone binary that walks a directory and runs the agentic
insight loop over every image/video, skipping files already processed.
Supports --path, --model, --max-iterations, --timeout-secs, --num-ctx,
and --reprocess flags for flexible overnight/VPS batch runs.

Also adds OllamaClient::with_request_timeout() builder method so slow
large models are not cut off by the default 120s limit.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-07 16:39:46 -04:00
Cameron
da039bbc49 fix: include files without EXIF when sorting by date
Date sorting previously used a DB-level query that acted as an inner join,
silently dropping files with no image_exif row. Replace it with the existing
in-memory sort which already falls back to filename-extracted and filesystem
dates, so all files appear in sorted results.

Also removes the now-unused get_files_sorted_by_date trait method and its
SqliteExifDao implementation and test mock.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-07 14:43:26 -04:00
Cameron
191ccc0d77 feat: add entity-relationship knowledge memory to agentic insights
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>
2026-04-03 17:27:49 -04:00
Cameron
b2cf99c857 feat: surface Ollama context token usage in agentic insight response
Captures prompt_eval_count and eval_count from Ollama /api/chat responses
during the agentic loop and returns them in POST /insights/generate/agentic
so the frontend can display context window usage to the user.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-03 17:25:35 -04:00
50cf526b46 Merge pull request '002-agentic-insights' (#53) from 002-agentic-insights into master
Reviewed-on: #53
2026-04-02 16:46:06 +00:00
Cameron
54a49a8562 fix: agentic loop robustness — tool arg sanitisation, geocoding, better errors
- Sanitise tool call arguments before re-sending in conversation history: non-object values (bool, string, null) that some models produce are normalised to {} to prevent Ollama 500s
- Map 'error parsing tool call' Ollama 500 to HTTP 400 with a descriptive message listing compatible models (llama3.1, llama3.2, qwen2.5, mistral-nemo)
- Add reverse_geocode tool backed by existing Nominatim helper; description hints model can chain it after get_location_history results
- Make get_sms_messages contact parameter optional (was required, forcing the model to guess); executor now passes None to fall back to all-contacts search
- Log tool result outcomes at warn level for errors/empty results, info for successes; log SMS API errors with full detail; log full request body on Ollama 500
- Strengthen system prompt to require 3-4 tool calls before final answer
- Try fallback server when checking model capabilities (primary-only check caused 500 for models only on fallback)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 23:58:01 -04:00
Cameron
c1b6013412 chore: cargo fmt + clippy fix for collapsed if-let chain (T017)
- cargo fmt applied across all modified source files
- Collapse nested if let Some / if !is_empty into a single let-chain (clippy::collapsible_match)
- All other warnings are pre-existing dead-code lint on unused trait methods

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 23:09:58 -04:00
Cameron
5c9f5c7d0b feat: add model-availability validation to agentic insight generation (T009-T011)
- Verify custom model exists on at least one configured server before starting agentic loop; returns HTTP 400 with descriptive error if not found
- has_tool_calling field auto-serialised in GET /insights/models via existing ModelCapabilities Serialize derive
- model_version stored from OllamaClient.primary_model (already correct in T006 implementation)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 23:07:43 -04:00
Cameron
091327e5d9 feat: add POST /insights/generate/agentic handler and route
Register the agentic insight endpoint that validates tool-calling capability,
runs the agentic loop, and returns the stored PhotoInsightResponse. Returns 400
for unsupported models, 500 for other errors. Max iterations configurable via
AGENTIC_MAX_ITERATIONS env var (default 10).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 23:01:25 -04:00
Cameron
7615b9c99b feat: add tool executors and generate_agentic_insight_for_photo() to InsightGenerator
Add 6 tool executor methods (search_rag, get_sms_messages, get_calendar_events,
get_location_history, get_file_tags, describe_photo) and the agentic loop that
uses Ollama's chat_with_tools API to let the model decide which context to gather
before writing the final photo insight.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 23:00:41 -04:00
Cameron
5e5a2a3167 feat: add tool-calling types, chat_with_tools(), and has_tool_calling capability detection
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 22:55:20 -04:00
Cameron
8196ef94a0 feat: photo-first RAG enrichment — early vision description + tags in RAG and search context
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 17:23:49 -04:00
Cameron
e58b8fe743 feat: add enrichment parameter to gather_search_context() replacing weak metadata query
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 17:17:21 -04:00
Cameron
c0d27d0b9e feat: add Tags section to combine_contexts() for insight context
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 17:14:00 -04:00
Cameron
8ecd3c6cf8 refactor: use Arc<Mutex<SqliteConnection>> in SqliteTagDao, remove unsafe impl Sync
Aligns SqliteTagDao with the pattern used by SqliteExifDao and SqliteInsightDao.
The unsafe impl Sync workaround is no longer needed since Arc<Mutex<>> provides
safe interior mutability and automatic Sync derivation.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 17:10:11 -04:00
Cameron
387ce23afd feat: add tag_dao to InsightGenerator for tag-based context enrichment
Threads SqliteTagDao through InsightGenerator and AppState (both default
and test_state). Adds Send+Sync bounds to TagDao trait with unsafe impls
for SqliteTagDao (always Mutex-protected) and TestTagDao (single-threaded).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 16:59:39 -04:00
Cameron
b31b4b903c refactor: use &str for generate_photo_description image parameter
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 16:56:27 -04:00
Cameron
dd0715c081 feat: add generate_photo_description() to OllamaClient for RAG enrichment
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-18 16:53:34 -04:00
c804ee39cb Merge pull request '001-video-wall' (#52) from 001-video-wall into master
Reviewed-on: #52
2026-03-02 18:45:03 +00:00
Cameron
c05a16f7f2 Add JSON error logging for failed request deserialization
Configures a global JsonConfig error handler that logs the method, URI,
and parse error details at WARN level before returning the 400 response.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-27 20:02:18 -05:00
Cameron
3982c6d6d4 Fix 10-bit encode not supported error with h264_nvenc
Add format=yuv420p to preview clip filter chains to convert 10-bit
sources to 8-bit before encoding, since NVENC doesn't support 10-bit
H.264.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-27 19:55:36 -05:00
27a148c0aa Merge branch 'master' into 001-video-wall 2026-02-27 19:06:55 +00:00
Cameron
5975828f65 Fix incorrect frame rate handling in preview clip generation 2026-02-26 10:58:27 -05:00
Cameron
36612444c5 Ensure we re-queue pending/failed records 2026-02-26 10:42:20 -05:00
Cameron
32ece84209 Fix high framerate preview playback 2026-02-26 10:26:52 -05:00
Cameron
7d164bad81 Fix import warnings 2026-02-26 10:10:26 -05:00
Cameron
0d05033b38 Add comprehensive testing for preview clip and status handling
- Implement unit tests for PreviewClipRequest/PreviewStatusRequest serialization and deserialization.
- Add tests for PreviewDao (insert, update, batch retrieval, and status-based queries).
- Extend Actix-web integration tests for `/video/preview/status` endpoint scenarios.
- Introduce in-memory TestPreviewDao for mock database interactions.
- Update README with new config parameters for preview clips.
2026-02-26 10:06:21 -05:00
Cameron
842ed4ed66 Add Speckit and Constitution 2026-02-26 10:05:47 -05:00
Cameron
19c099360e Add VideoWall feature: server-side preview clip generation and mobile grid view
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>
2026-02-25 19:40:17 -05:00
cdc2eef833 Merge pull request 'Build insight title from generated summary' (#51) from feature/insight-tweaks into master
Reviewed-on: #51
2026-02-24 21:21:20 +00:00
Cameron
7a0da1ab4a Build insight title from generated summary 2026-02-24 16:08:25 -05:00
1fb3441a38 Merge pull request 'Fix video rotation' (#50) from feature/fix-video-rotation into master
Reviewed-on: #50
2026-02-10 02:54:46 +00:00
Cameron
39c66d81cc Fix video rotation 2026-02-05 18:39:36 -05:00
0d5c141328 Merge pull request 'Expand temporal context window for SMS retrieval from ±2 days to ±4 days' (#49) from feature/increase-insight-context into master
Reviewed-on: #49
2026-02-05 20:57:46 +00:00
Cameron
e92513fbe9 Expand temporal context window for SMS retrieval from ±2 days to ±4 days 2026-01-29 19:48:09 -05:00
92a468233e Merge pull request 'feature/gps-map-support' (#48) from feature/gps-map-support into master
Reviewed-on: #48
2026-01-28 15:54:18 +00:00
Cameron
1efdd02eda Add GPS summary sorting
Run cargo fmt/clippy
2026-01-28 10:52:17 -05:00
Cameron
7d2a3148bb Make Memories week span sorting chronological 2026-01-26 20:51:11 -05:00
Cameron
a6cc64ece0 Bump to version 0.5.2 2026-01-26 20:05:42 -05:00
Cameron
1d2f4e3441 Add circular thumbnail creation for Map view 2026-01-26 20:04:14 -05:00
Cameron
073b5ed418 Added gps-summary endpoint for Map integration 2026-01-26 11:58:24 -05:00
701a06871c Merge pull request 'feature/search-performance' (#47) from feature/search-performance into master
Reviewed-on: #47
2026-01-26 16:03:57 +00:00
Cameron
c9410c9c91 Add rotation check to video transcoding logic
Seems like vertical videos aren't preserving rotation logic on copy.
2026-01-26 10:55:15 -05:00
Cameron
08f402d4d1 Add h264 codec detection and orphaned playlist cleanup job
Implement `is_h264_encoded` to detect existing h264 videos and optimize processing by using stream copy when possible. Introduce a background job for cleaning up orphaned playlists and segments based on missing source videos. Improve checks for playlist generation necessity.
2026-01-19 22:37:50 -05:00
Cameron
9245778391 Generate video playlists on period directory scans 2026-01-19 22:32:00 -05:00
Cameron
ea53932b4b Update Cargo.lock for version bump 2026-01-18 19:26:23 -05:00
Cameron Cordes
85e6567674 Bump to 0.5.1 2026-01-18 19:17:53 -05:00
Cameron
be483c9c1a Add database optimizations for photo search and pagination
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.
2026-01-18 19:17:10 -05:00
5e646dfc19 Merge pull request 'feature/insights' (#46) from feature/insights into master
Reviewed-on: #46
2026-01-15 01:07:57 +00:00
Cameron
e31d5716b6 Additional cleanup and warning fixing 2026-01-14 15:21:44 -05:00
Cameron
02ca60a5d0 Remove individual messages embedding SQL 2026-01-14 14:23:50 -05:00
Cameron
af35a996a3 Cleanup unused message embedding code
Fixup some warnings
2026-01-14 13:33:36 -05:00
Cameron
e2d6cd7258 Run clippy fix 2026-01-14 13:17:58 -05:00
Cameron
e9729e9956 Fix unused import from binary from getting removed with cargo fix 2026-01-14 13:13:06 -05:00
Cameron
b7582e69a0 Add model capability caching and clear functions 2026-01-14 13:12:09 -05:00
Cameron
f65f4efde8 Make date parse from metadata a little more consistent 2026-01-14 12:54:36 -05:00
Cameron
a37a211282 Fix upload with missing file name or space in filename 2026-01-11 21:15:41 -05:00
Cameron
ad0bba63b4 Add check for vision capabilities 2026-01-11 15:22:24 -05:00
Cameron
5b35df4007 Remove unused function 2026-01-11 14:42:25 -05:00
Cameron
fa600f1c2c Fallback to sorting by Metadata date 2026-01-11 14:39:50 -05:00
Cameron
0efa8269a1 Fix test 2026-01-10 11:34:16 -05:00
Cameron
b2cc617bc2 Pass image as additional Insight context 2026-01-10 11:30:01 -05:00
Cameron
084994e0b5 Daily Summary Embedding Testing 2026-01-08 13:41:32 -05:00
Cameron
61e10f7678 Improve Exif Query path handling 2026-01-08 13:41:08 -05:00
Cameron
cd66521c17 Phase 3: Integrate Google Takeout context into InsightGenerator
- Updated InsightGenerator struct with calendar, location, and search DAOs
- Implemented hybrid context gathering methods:
  * gather_calendar_context(): ±7 days with semantic ranking
  * gather_location_context(): ±30 min with GPS proximity check
  * gather_search_context(): ±30 days semantic search
- Added haversine_distance() utility for GPS calculations
- Updated generate_insight_for_photo_with_model() to use multi-source context
- Combined all context sources (SMS + Calendar + Location + Search) with equal weight
- Initialized new DAOs in AppState (both default and test implementations)
- All contexts are optional (graceful degradation if data missing)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-05 14:57:31 -05:00
Cameron
d86b2c3746 Add Google Takeout data import infrastructure
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>
2026-01-05 14:50:49 -05:00
Cameron
bb23e6bb25 Cargo fix 2026-01-05 10:31:34 -05:00
Cameron
ad07f5a1fa Update README 2026-01-05 10:09:18 -05:00
Cameron
11e725c443 Enhanced Insights with daily summary embeddings
Bump to 0.5.0. Added daily summary generation job
2026-01-05 09:13:16 -05:00
Cameron
43b7c2b8ec Remove dialoguer dependency 2026-01-03 20:32:00 -05:00
Cameron
cbbfb7144b Re-enable video GIF generation 2026-01-03 20:31:18 -05:00
Cameron
cf52d4ab76 Add Insights Model Discovery and Fallback Handling 2026-01-03 20:27:34 -05:00
Cameron
1171f19845 Create Insight Generation Feature
Added integration with Messages API and Ollama
2026-01-03 10:30:37 -05:00
Cameron
0dfec4c8c5 Fix memory filename date extraction 2026-01-02 19:29:42 -05:00
878465fea9 Merge pull request 'Implement critical security improvements for authentication' (#45) from feature/security-improvements into master
Reviewed-on: #45
2026-01-02 22:01:39 +00:00
Cameron
4d9addaf22 Add filename date to metadata if available 2025-12-29 21:54:25 -05:00
Cameron
2d915518e2 Bump to 0.4.1 2025-12-29 19:51:21 -05:00
Cameron
2d02f00e7d Fix Memories Week span sorting 2025-12-29 18:49:52 -05:00
Cameron
54e23a29b3 Fix warnings 2025-12-29 14:29:29 -05:00
Cameron
9cb923df9e Fix memory date priority 2025-12-29 12:28:17 -05:00
Cameron
2c52cffd65 Implement critical security improvements for authentication
This commit addresses several security vulnerabilities in the authentication
and authorization system:

1. JWT Encoding Panic Fix (Critical)
   - Replace .unwrap() with proper error handling in JWT token generation
   - Prevents server crashes from encoding failures
   - Returns HTTP 500 with error logging instead of panicking

2. Rate Limiting for Login Endpoint (Critical)
   - Add actix-governor dependency (v0.5)
   - Configure rate limiter: 2 requests/sec with burst of 5
   - Protects against brute-force authentication attacks

3. Strengthen Password Requirements
   - Minimum length increased from 6 to 12 characters
   - Require uppercase, lowercase, numeric, and special characters
   - Add comprehensive validation with clear error messages

4. Fix Token Parsing Vulnerability
   - Replace unsafe split().last().unwrap_or() pattern
   - Use strip_prefix() for proper Bearer token validation
   - Return InvalidToken error for malformed Authorization headers

5. Improve Authentication Logging
   - Sanitize error messages to avoid leaking user existence
   - Change from "User not found or incorrect password" to "Failed login attempt"

All changes tested and verified with existing test suite (65/65 tests passing).

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2025-12-26 23:53:54 -05:00
a2f2d4de5c Merge pull request 'feature/exif-endpoint' (#44) from feature/exif-endpoint into master
Reviewed-on: #44
2025-12-27 03:25:17 +00:00
Cameron
ccd16ba987 Files endpoint refactoring 2025-12-26 22:20:01 -05:00
Cameron
be281130d5 Send timestamp from filename for Memories endpoint 2025-12-25 23:32:00 -05:00
Cameron
ae0886cd2e Fix tag count sorting, hopefully 2025-12-25 15:17:50 -05:00
Cameron
6c543ffa68 Add CLAUDE.md documentation for Claude Code
Comprehensive guide covering build commands, architecture overview, database patterns, file processing pipeline, API structure, and development workflows.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2025-12-24 16:07:03 -05:00
Cameron
f0d482af12 Optimize release build times with thin LTO
Switch from fat LTO to thin LTO for faster release builds while maintaining similar performance characteristics.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2025-12-24 10:21:47 -05:00
Cameron
c0021734b6 Try fixing Otel span propogation 2025-12-24 10:17:14 -05:00
Cameron
c1cfda9df9 Fix memories week span sorting 2025-12-24 00:27:44 -05:00
Cameron
c035678162 Add tracing to EXIF DAO methods 2025-12-23 22:57:24 -05:00
Cameron
636701a69e Refactor file type checking for better consistency
Fix tests
2025-12-23 22:30:53 -05:00
Cameron
6dbac6f22f Run cargo fmt/fix 2025-12-23 22:07:50 -05:00
Cameron
3a64b30621 Fix Date sorting in tagged/recursive search 2025-12-23 22:07:40 -05:00
Cameron
47d3ad7222 Add polling-based file watching
Remove notify and update otel creates
2025-12-22 22:54:19 -05:00
Cameron
df94010d21 Fix tests and improve memories date error log 2025-12-19 14:20:51 -05:00
Cameron
e3ccc123d0 Add EXIF update support 2025-12-18 21:20:45 -05:00
Cameron
b4c5a38c9d Cargo fmt 2025-12-18 21:20:31 -05:00
Cameron
aaf9cc64be Add Cleanup binary for fixing broken DB/file relations 2025-12-18 16:02:15 -05:00
Cameron
28d85dc4a5 Fix recursive search and media filtering 2025-12-18 11:25:50 -05:00
Cameron
721b66481e Add EXIF search implementation to list photos endpoint 2025-12-18 10:06:13 -05:00
Cameron
eb8e08b9ff Add EXIF search infrastructure (Phase 1 & 2)
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()
2025-12-18 09:34:07 -05:00
Cameron
52e1ced2a2 Improved image caching and CORS handling 2025-12-17 22:36:03 -05:00
Cameron
c6b1b46629 Fix video part directory traversal 2025-12-17 22:32:46 -05:00
Cameron
7ddc2dec64 Add indexes for favorite de-duplication 2025-12-17 22:31:16 -05:00
Cameron
1294a86a41 Add indexes for improved query performance 2025-12-17 22:31:04 -05:00
Cameron
445b82b21a Bump to 0.4.0 2025-12-17 22:17:54 -05:00
Cameron
c7fd328925 Check Exif DB for memory collection 2025-12-17 22:10:23 -05:00
Cameron
e4d988a9fd Cargo formatting 2025-12-17 22:10:03 -05:00
Cameron
d61fcb942a Exif comment on TZ handling 2025-12-17 22:09:03 -05:00
Cameron
07c27bf1bb Add HEIC and TIF image extensions to files endpoint 2025-12-17 16:57:27 -05:00
Cameron
4082f1fdb8 Add Exif storing and update to Metadata endpoint 2025-12-17 16:55:48 -05:00
4851f64229 Merge pull request 'Added file date format for memories' (#43) from feature/new-memories-filename-format into master
Reviewed-on: #43
2025-12-01 18:53:23 +00:00
Cameron
3c894335ce Added file date format for memories 2025-12-01 13:51:17 -05:00
b58fc0034c Merge pull request 'feature/improve-memories-exclude' (#42) from feature/improve-memories-exclude into master
Reviewed-on: #42
2025-12-01 18:07:07 +00:00
Cameron
f02a858368 Bump to 0.3.1 and format/clippy 2025-12-01 13:04:55 -05:00
Cameron
a7d065aadc Tests and improved pattern-excluding behavior 2025-12-01 12:54:40 -05:00
Cameron
f5c53d1e0e Allow for pattern-based memories folder exclusion 2025-12-01 12:29:32 -05:00
6aefea3a27 Merge pull request 'feature/rust-2024-edition' (#41) from feature/rust-2024-edition into master
Reviewed-on: #41
2025-09-01 17:47:51 +00:00
Cameron
273b877e16 Update to Rust 2024 edition
Formatted code.
2025-09-01 13:36:27 -04:00
Cameron
0d05b283ce Cargo update 2025-09-01 13:28:37 -04:00
5021b3218d Merge pull request 'Just look for date format instead of screenshot text' (#40) from feature/fix-screenshot-date-regex into master
Reviewed-on: #40
2025-09-01 15:15:49 +00:00
Cameron
2cc4124544 Just look for date format instead of screenshot text 2025-09-01 11:15:27 -04:00
ed9071d41d Merge pull request 'Add additional memories filename regex' (#39) from feature/additional-memories-date-format into master
Reviewed-on: #39
2025-09-01 15:09:41 +00:00
Cameron
6f76a74b2e Add additional memories filename regex 2025-09-01 11:09:09 -04:00
a79bccc751 Merge pull request 'Add additional memories filename regex' (#38) from feature/add-memories-file-date-regex into master
Reviewed-on: #38
2025-09-01 15:01:40 +00:00
Cameron
9c04fcb1d1 Add additional memories filename regex 2025-09-01 11:01:01 -04:00
6336c321c7 Merge pull request 'Allow for excluding directories from Memories endpoint' (#37) from feature/memories-ignore-dirs into master
Reviewed-on: #37
2025-08-28 17:06:44 +00:00
Cameron
2f91dbdc2e Update README 2025-08-28 11:36:16 -04:00
Cameron
f27b22ead4 Update README 2025-08-28 11:35:41 -04:00
Cameron
e46953194e Allow for excluding directories from Memories endpoint 2025-08-27 16:02:32 -04:00
5277465f9e Merge pull request 'Use rayon for memories endpoint' (#36) from feature/memories-parallel into master
Reviewed-on: #36
2025-08-21 20:44:50 +00:00
Cameron
34784a39f6 Use rayon for memories endpoint 2025-08-21 16:39:33 -04:00
c325676af1 Merge pull request 'feature/memories' (#35) from feature/memories into master
Reviewed-on: #35
2025-08-16 16:42:38 +00:00
Cameron
544256f658 Bump to 0.3.0 2025-08-15 23:22:05 -04:00
Cameron
93957bf389 Refactor date parsing from filename by introducing reusable closure, remove redundant logging level, and simplify regex logic. 2025-08-15 23:20:07 -04:00
Cameron
8114204485 Update Otel 2025-08-15 23:18:53 -04:00
Cameron
7dcf89c47e Add conditional sorting logic for Month span in memories sorting 2025-08-15 17:22:01 -04:00
Cameron
4315744abb Improve Memory sorting 2025-08-13 13:23:32 -04:00
Cameron
85093ff0c7 Add parsing date from filename for memories 2025-08-12 20:55:22 -04:00
Cameron
8d9a5fd79f Try adding timezone awareness 2025-08-11 17:11:02 -04:00
Cameron
6aa3c932fb Run cargo fmt 2025-08-11 17:08:24 -04:00
Cameron
88114ef4d4 Add Month memory filter span 2025-08-09 22:46:25 -04:00
Cameron
caed787c04 Add /memories endpoint 2025-08-09 22:24:48 -04:00
Cameron
b3a885de28 Run cargo fmt 2025-08-08 15:06:43 -04:00
bf3c26a5f1 Merge pull request 'Video Gifs' (#34) from feature/video-gifs into master
Reviewed-on: #34
2025-08-08 18:55:13 +00:00
Cameron
2ea36a4c9b Get tests building and sort of passing 2025-07-17 20:32:23 -04:00
Cameron
264195d3a2 Cleanup warnings 2025-07-17 20:08:12 -04:00
Cameron
e5afdd909b Serve video gifs when requested 2025-07-02 15:48:49 -04:00
Cameron
3fbdba2b9c Merge branch 'master' into feature/video-gifs 2025-06-16 21:06:38 -04:00
8dae25606d Merge pull request 'Recursive Sorting fix and many logging/tracing enhancements' (#33) from feature/fix-recursive-sort into master
Reviewed-on: #33
2025-06-12 20:03:20 +00:00
Cameron
97a07e11ca Fix SQL injection vulnerability in a tag query 2025-06-12 15:01:07 -04:00
Cameron
a25ffcc351 Add enhanced logging and tracing for playlist generation 2025-06-12 13:12:01 -04:00
Cameron
2c553a8016 Additional logging and tracing enhancements 2025-06-04 15:05:23 -04:00
Cameron
7c882fd31c Add webp files and improve logging 2025-06-03 15:23:39 -04:00
Cameron
6aff7f456a Manually pass the current context around 2025-06-03 14:06:19 -04:00
Cameron
c4153b404c Try using current context 2025-06-03 13:02:25 -04:00
Cameron
b11d647ffa Try fixing span context for db call tracing 2025-06-03 12:51:37 -04:00
Cameron
1e63e0c08c Add DB spans to the various queries 2025-06-03 12:07:26 -04:00
Cameron
785ce157e6 Get Otel span from the request 2025-05-23 18:24:54 -04:00
Cameron
d37deb36fe Additional Otel logging and spans 2025-05-23 14:51:54 -04:00
Cameron
24d2123fc2 Fix recursive-any tag counting
This is bad security wise so it'll need another pass.
2025-05-18 19:57:16 -04:00
Cameron
fe0446a43f Merge branch 'master' into feature/video-gifs
# Conflicts:
#	Cargo.toml
#	src/files.rs
#	src/main.rs
2025-05-17 15:57:01 -04:00
a79162c66a Merge pull request 'feature/sort-by-tag-count' (#32) from feature/sort-by-tag-count into master
Reviewed-on: #32
2025-05-17 17:47:02 +00:00
Cameron
484eec8b39 Only use Otel on release builds 2025-05-17 13:41:30 -04:00
Cameron
5b17fba51f Add sorting by a File's Tag Count 2025-05-17 13:41:14 -04:00
f216723df0 Merge pull request 'feature/otel-telemetry' (#31) from feature/otel-telemetry into master
Reviewed-on: #31
2025-05-07 00:26:26 +00:00
Cameron
518fba0ef5 Add missing otel.rs 2025-05-06 20:26:02 -04:00
Cameron
d6451ee782 Add Simple OpenTelemetry setup 2025-05-06 20:15:03 -04:00
Cameron
399f5f2336 Add ability to create summary clips of existing videos 2024-12-14 20:55:10 -05:00
Cameron
0edb0dbdd1 Cleanup 2024-12-07 21:53:39 -05:00
Cameron
b2a361faba First pass on creating gifs from a video 2024-12-07 21:49:33 -05:00
Cameron
4e4a2240cf Move video.rs into its own module 2024-12-07 21:46:37 -05:00
f99360cd9e Merge pull request 'feature/shuffle-sort' (#30) from feature/shuffle-sort into master
Reviewed-on: #30
2024-12-06 16:25:42 +00:00
Cameron
3ce1b84604 Sort on recursive search
Run clippy
2024-12-06 11:21:42 -05:00
Cameron
4a91c6344a Use exclude subquery for recursive all tag search 2024-12-06 11:04:08 -05:00
Cameron
ff13a57d0e Try subquery for excluding tags 2024-12-06 10:58:40 -05:00
Cameron
03f3756ffd Remove tag count from any tag query 2024-12-06 09:54:53 -05:00
Cameron
787d1fd5d0 Fix recursive search at the root, cleanup video generation return 2024-12-06 09:47:21 -05:00
Cameron
8bc9c5585e log ffmpeg output and cleanup video creation 2024-12-05 20:47:51 -05:00
Cameron
04a7cb417f Bump app version to 0.2.0 2024-12-05 20:30:45 -05:00
Cameron
18ba5796b0 Update to rust 2021
Fix tests
2024-12-05 20:27:01 -05:00
Cameron
9c2cd2566f Prepare for rust edition 2021 2024-12-05 20:25:00 -05:00
Cameron
8daa35b5a7 Fix recursive search when beneath top level directory 2024-12-05 20:19:38 -05:00
Cameron
0419aa2323 Scan and generate Video HLS playlists on startup
Refactored and improved video path state. Bumped versions of some dependencies.
2024-12-05 20:19:03 -05:00
Cameron
2b2a811cae Fix recursive filtering under base path 2024-12-04 19:50:04 -05:00
Cameron
b7f13d4cbf Fix exclude filtering for any tags 2024-12-04 19:42:00 -05:00
Cameron
d280db8482 Fix exclude filtering 2024-11-27 16:42:17 -05:00
Cameron
0af7c8f98b Fix missing return and update test signatures 2024-11-27 15:43:27 -05:00
Cameron
9327208deb Remove filtering when recursively searching with tags 2024-11-25 21:40:25 -05:00
Cameron
a668b14116 Update deprecated functions 2024-11-24 12:56:21 -05:00
Cameron
860e7a97fb Use TagDao for improved filtering 2024-11-24 09:49:03 -05:00
Cameron
9a32a1cfe7 Allow for excluding certain tags from a file search 2024-11-23 20:21:19 -05:00
Cameron
6986540295 Add sorting shuffle, and name asc/desc 2024-11-23 19:13:25 -05:00
Cameron
287a61ae3f Update dependencies, improve startup logging 2024-11-23 12:14:12 -05:00
4899dc4967 Merge pull request 'Use PhotoSize enum in file requests' (#29) from feature/photosize-enum into master
Reviewed-on: #29
2024-06-30 21:51:28 +00:00
Cameron Cordes
9a486b3f66 Use PhotoSize enum in file requests 2024-06-30 17:49:55 -04:00
a403903807 Merge pull request 'Trim spaces from new tags' (#28) from feature/trim-new-tags into master
Reviewed-on: #28
2024-03-21 02:17:32 +00:00
Cameron Cordes
1881b9efb9 Trim spaces from new tags
Fix unit test build
2024-03-20 22:16:06 -04:00
8eea6670c8 Merge pull request 'Fix recursive searching with tags' (#27) from feature/fix-recursive-tag-search into master
Reviewed-on: #27
2024-03-11 00:46:55 +00:00
Cameron Cordes
3925d835f6 Fix recursive searching with tags 2024-03-10 20:45:18 -04:00
3c9263eb48 Merge pull request 'feature/add-recursive-tag-support' (#26) from feature/add-recursive-tag-support into master
Reviewed-on: #26
2024-03-09 18:14:49 +00:00
Cameron Cordes
05a56ba0bd Fix Recursive searching with tags including Any and All filter modes 2024-03-09 13:11:55 -05:00
Cameron Cordes
b2c8ebe558 Break-up FilterMode.All being recursive
Filtering on tags needs some reworking to handle recursive with All or Any
filtering.
2024-03-07 19:01:46 -05:00
Cameron Cordes
ef39359862 Add basic recursive tag searching support based on the search path 2024-03-07 17:56:50 -05:00
d58e34c18f Merge pull request 'Refresh thumbnails after an upload or file move' (#25) from feature/refresh-thumbnails-improvements into master
Reviewed-on: #25
2024-02-22 02:48:57 +00:00
Cameron Cordes
30dba33e47 Refresh thumbnails after an upload or file move 2024-02-21 17:24:16 -05:00
446d2e53ee Merge pull request 'Ensure Move endpoint does not overwrite an existing file' (#24) from feature/fix-file-move-overwrite into master
Reviewed-on: #24
2024-01-22 02:37:29 +00:00
Cameron Cordes
0faad2fbdb Ensure Move endpoint does not overwrite an existing file 2024-01-21 21:35:36 -05:00
df843ba30a Merge pull request 'Add Move File functionality and endpoint' (#23) from feature/file-move-endpoint into master
Reviewed-on: #23
2024-01-22 02:14:33 +00:00
Cameron Cordes
419dd7e7e5 Add Move File functionality and endpoint 2024-01-21 21:10:13 -05:00
2f9ad6b24f Merge pull request 'Add the count of tagged files to All tags endpoint' (#21) from feature/include-tag-counts into master
Reviewed-on: #21
2024-01-18 03:54:38 +00:00
Cameron Cordes
17012fc447 Merge branch 'master' into feature/include-tag-counts 2024-01-17 22:47:46 -05:00
ae0bb79bc4 Merge pull request 'feature/handle-duplicate-file-name-upload' (#22) from feature/handle-duplicate-file-name-upload into master
Reviewed-on: #22
2024-01-18 03:40:22 +00:00
Cameron Cordes
5bbc775d3a Update to Watcher 6
Improve upload performance by relying on the file watcher instead of
synchronously creating thumbnails before responding to the client.
2024-01-17 22:25:18 -05:00
Cameron Cordes
195d522f64 Add file upload log in happy path and update log level for duplicate path 2024-01-17 21:00:15 -05:00
Cameron Cordes
6c5014253f Update gitignore and RustRover config 2024-01-17 20:49:31 -05:00
Cameron Cordes
bf7fb810de Fix duplicate file naming 2024-01-17 20:45:36 -05:00
Cameron Cordes
7e11448ada Update dependencies 2023-12-02 14:23:51 -05:00
Cameron Cordes
2b9a741642 Account for current path for tag counts
Fix tag unit tests
2023-12-02 13:38:24 -05:00
Cameron Cordes
da21f064b9 Add the count of tagged files to All tags endpoint 2023-12-01 23:01:03 -05:00
Cameron Cordes
9e8f02240f Put timestamp in file name if uploaded file already exists 2023-04-30 11:37:23 -04:00
5228cb14e0 Merge pull request 'feature/tagging' (#16) from feature/tagging into master
Reviewed-on: #16
2023-04-10 12:55:27 +00:00
Cameron Cordes
8bcd837038 Fix file upload
Add a flag for new files so we can skip the exists check when seeing if
the new file is within the base directory.
2023-04-03 08:41:03 -04:00
Cameron Cordes
7863990c68 Run clippy 2023-03-25 20:59:32 -04:00
Cameron Cordes
a9109fc52d Add the ability to query files by tags independent of file path 2023-03-25 20:52:51 -04:00
Cameron Cordes
ae2642a544 Fix warnings, and general code cleanup 2023-03-25 20:52:20 -04:00
Cameron Cordes
ae8665f632 Fix clippy warnings 2023-03-22 15:17:48 -04:00
Cameron Cordes
4ded708911 Extract FileSystem to a trait for better testability
Added some tests around filtering and searching by Tags. Added the
ability to use an in-memory Sqlite DB for more integration tests.
2023-03-22 15:17:33 -04:00
Cameron Cordes
5a2dce85e8 Fix searching by tags and fixed All FilterMode
Manually parsing the tag_ids for the file filtering isn't amazing, but
this works in a more friendly format.

Also the All filter mode was set up in the wrong direction instead of
checking that the file had ALL the tag ids provided, it checked that all
the tag-ids were on a file, which is too restrictive and wouldn't show
many files. Perhaps an ONLY option could exist for being even more
specific.
2023-03-22 13:58:14 -04:00
Cameron Cordes
02444de7fa Fix tagging file with new tag
When tagging a file with a brand new tag, we were using the number of
rows affected as the ID instead of doing the query for the ID of the row
we just inserted, this should fix when we tag a photo with a new tag.
2023-03-22 13:51:32 -04:00
Cameron Cordes
7d05c9b8bf Add filtering by Tag to /images endpoint 2023-03-20 08:14:12 -04:00
Cameron Cordes
de4041bd17 Refactor tags services and added tests
Implemented some functionality which will allow the service
configuration of the app to be split among the features for readability
and testability.
2023-03-19 15:05:20 -04:00
Cameron Cordes
fbcfc68e01 Fix tests 2023-03-19 12:29:33 -04:00
Cameron Cordes
8bcd9440bf Add Endpoint for Batch add/removal of tags on a file 2023-03-19 12:13:04 -04:00
Cameron Cordes
f98d3261a7 Fix tags all and tags for photo endpoints 2023-03-18 21:00:26 -04:00
Cameron Cordes
68bfcbf85f Update and Migrate Diesel to 2.0
Almost have tag support working, still figuring out how to get photo
tags.
2023-03-18 14:43:41 -04:00
Cameron Cordes
40c79d13db Move tags to their own module
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2022-03-17 22:07:33 -04:00
Cameron Cordes
c8cae28c9f Merge branch 'master' into feature/tagging 2022-03-17 21:53:17 -04:00
d0536c8980 Merge pull request 'Improve testability and remove boxing' (#20) from feature/testing-improvements into master
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Core Repos/ImageApi/pipeline/head This commit looks good
Reviewed-on: #20
2022-03-18 00:25:51 +00:00
Cameron Cordes
528db5da3a Move app state to its own module
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2022-03-17 19:40:07 -04:00
Cameron Cordes
4d9b7c91a1 Improve testability and remove boxing
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Leverage generics to remove the extra heap allocation for the response
handlers using Dao's. Also moved some of the environment variables to
app state to allow for easier testing.
2022-03-16 20:51:37 -04:00
e02165082a Merge pull request 'Update to Actix 4' (#19) from feature/update-to-actix-4 into master
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Reviewed-on: #19
2022-03-02 02:32:29 +00:00
Cameron Cordes
50e973da1f Cleanup unused imports
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2022-03-01 21:16:04 -05:00
Cameron Cordes
b219663e0a Update CI to Rust 1.59
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This will support Rust 2021 edition for Actix 4.
2022-03-01 20:44:51 -05:00
Cameron Cordes
69fe307516 Update to Actix 4
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2022-03-01 20:38:41 -05:00
Cameron Cordes
9cd19d03eb Create Delete Tag endpoint
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2021-11-30 20:07:00 -05:00
1e3f33c2d3 Merge pull request 'Update Rust image to 1.55' (#17) from feature/update-ci-rust-155 into master
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Reviewed-on: #17
2021-10-13 16:41:15 +00:00
Cameron Cordes
f0e96071be Update Rust image to 1.55
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2021-10-13 12:12:25 -04:00
Cameron Cordes
14ab02a1ec Elevate insertion logs to info and fix error logs
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Core Repos/ImageApi/pipeline/pr-master This commit looks good
2021-10-11 21:52:06 -04:00
Cameron Cordes
2e5ac8861c Add created timestamps for tags 2021-10-11 21:52:06 -04:00
Cameron Cordes
9d925be84d Improve add tag endpoint and add get tag endpoint
Flattened out the add tag logic to make it more functional.
2021-10-11 21:52:06 -04:00
Cameron Cordes
8939ffbaf5 Create Tag tables and Add Tag endpoint 2021-10-11 21:52:06 -04:00
Cameron Cordes
2d6db6d059 Update dependencies 2021-10-11 21:52:06 -04:00
198 changed files with 58720 additions and 2189 deletions

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[target.x86_64-unknown-linux-gnu]
linker = "/usr/bin/gcc"
rustflags = ["-C", "link-arg=-fuse-ld=mold"]

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---
description: Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Goal
Identify inconsistencies, duplications, ambiguities, and underspecified items across the three core artifacts (`spec.md`, `plan.md`, `tasks.md`) before implementation. This command MUST run only after `/speckit.tasks` has successfully produced a complete `tasks.md`.
## Operating Constraints
**STRICTLY READ-ONLY**: Do **not** modify any files. Output a structured analysis report. Offer an optional remediation plan (user must explicitly approve before any follow-up editing commands would be invoked manually).
**Constitution Authority**: The project constitution (`.specify/memory/constitution.md`) is **non-negotiable** within this analysis scope. Constitution conflicts are automatically CRITICAL and require adjustment of the spec, plan, or tasks—not dilution, reinterpretation, or silent ignoring of the principle. If a principle itself needs to change, that must occur in a separate, explicit constitution update outside `/speckit.analyze`.
## Execution Steps
### 1. Initialize Analysis Context
Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json -RequireTasks -IncludeTasks` once from repo root and parse JSON for FEATURE_DIR and AVAILABLE_DOCS. Derive absolute paths:
- SPEC = FEATURE_DIR/spec.md
- PLAN = FEATURE_DIR/plan.md
- TASKS = FEATURE_DIR/tasks.md
Abort with an error message if any required file is missing (instruct the user to run missing prerequisite command).
For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
### 2. Load Artifacts (Progressive Disclosure)
Load only the minimal necessary context from each artifact:
**From spec.md:**
- Overview/Context
- Functional Requirements
- Non-Functional Requirements
- User Stories
- Edge Cases (if present)
**From plan.md:**
- Architecture/stack choices
- Data Model references
- Phases
- Technical constraints
**From tasks.md:**
- Task IDs
- Descriptions
- Phase grouping
- Parallel markers [P]
- Referenced file paths
**From constitution:**
- Load `.specify/memory/constitution.md` for principle validation
### 3. Build Semantic Models
Create internal representations (do not include raw artifacts in output):
- **Requirements inventory**: Each functional + non-functional requirement with a stable key (derive slug based on imperative phrase; e.g., "User can upload file" → `user-can-upload-file`)
- **User story/action inventory**: Discrete user actions with acceptance criteria
- **Task coverage mapping**: Map each task to one or more requirements or stories (inference by keyword / explicit reference patterns like IDs or key phrases)
- **Constitution rule set**: Extract principle names and MUST/SHOULD normative statements
### 4. Detection Passes (Token-Efficient Analysis)
Focus on high-signal findings. Limit to 50 findings total; aggregate remainder in overflow summary.
#### A. Duplication Detection
- Identify near-duplicate requirements
- Mark lower-quality phrasing for consolidation
#### B. Ambiguity Detection
- Flag vague adjectives (fast, scalable, secure, intuitive, robust) lacking measurable criteria
- Flag unresolved placeholders (TODO, TKTK, ???, `<placeholder>`, etc.)
#### C. Underspecification
- Requirements with verbs but missing object or measurable outcome
- User stories missing acceptance criteria alignment
- Tasks referencing files or components not defined in spec/plan
#### D. Constitution Alignment
- Any requirement or plan element conflicting with a MUST principle
- Missing mandated sections or quality gates from constitution
#### E. Coverage Gaps
- Requirements with zero associated tasks
- Tasks with no mapped requirement/story
- Non-functional requirements not reflected in tasks (e.g., performance, security)
#### F. Inconsistency
- Terminology drift (same concept named differently across files)
- Data entities referenced in plan but absent in spec (or vice versa)
- Task ordering contradictions (e.g., integration tasks before foundational setup tasks without dependency note)
- Conflicting requirements (e.g., one requires Next.js while other specifies Vue)
### 5. Severity Assignment
Use this heuristic to prioritize findings:
- **CRITICAL**: Violates constitution MUST, missing core spec artifact, or requirement with zero coverage that blocks baseline functionality
- **HIGH**: Duplicate or conflicting requirement, ambiguous security/performance attribute, untestable acceptance criterion
- **MEDIUM**: Terminology drift, missing non-functional task coverage, underspecified edge case
- **LOW**: Style/wording improvements, minor redundancy not affecting execution order
### 6. Produce Compact Analysis Report
Output a Markdown report (no file writes) with the following structure:
## Specification Analysis Report
| ID | Category | Severity | Location(s) | Summary | Recommendation |
|----|----------|----------|-------------|---------|----------------|
| A1 | Duplication | HIGH | spec.md:L120-134 | Two similar requirements ... | Merge phrasing; keep clearer version |
(Add one row per finding; generate stable IDs prefixed by category initial.)
**Coverage Summary Table:**
| Requirement Key | Has Task? | Task IDs | Notes |
|-----------------|-----------|----------|-------|
**Constitution Alignment Issues:** (if any)
**Unmapped Tasks:** (if any)
**Metrics:**
- Total Requirements
- Total Tasks
- Coverage % (requirements with >=1 task)
- Ambiguity Count
- Duplication Count
- Critical Issues Count
### 7. Provide Next Actions
At end of report, output a concise Next Actions block:
- If CRITICAL issues exist: Recommend resolving before `/speckit.implement`
- If only LOW/MEDIUM: User may proceed, but provide improvement suggestions
- Provide explicit command suggestions: e.g., "Run /speckit.specify with refinement", "Run /speckit.plan to adjust architecture", "Manually edit tasks.md to add coverage for 'performance-metrics'"
### 8. Offer Remediation
Ask the user: "Would you like me to suggest concrete remediation edits for the top N issues?" (Do NOT apply them automatically.)
## Operating Principles
### Context Efficiency
- **Minimal high-signal tokens**: Focus on actionable findings, not exhaustive documentation
- **Progressive disclosure**: Load artifacts incrementally; don't dump all content into analysis
- **Token-efficient output**: Limit findings table to 50 rows; summarize overflow
- **Deterministic results**: Rerunning without changes should produce consistent IDs and counts
### Analysis Guidelines
- **NEVER modify files** (this is read-only analysis)
- **NEVER hallucinate missing sections** (if absent, report them accurately)
- **Prioritize constitution violations** (these are always CRITICAL)
- **Use examples over exhaustive rules** (cite specific instances, not generic patterns)
- **Report zero issues gracefully** (emit success report with coverage statistics)
## Context
$ARGUMENTS

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---
description: Generate a custom checklist for the current feature based on user requirements.
---
## Checklist Purpose: "Unit Tests for English"
**CRITICAL CONCEPT**: Checklists are **UNIT TESTS FOR REQUIREMENTS WRITING** - they validate the quality, clarity, and completeness of requirements in a given domain.
**NOT for verification/testing**:
- ❌ NOT "Verify the button clicks correctly"
- ❌ NOT "Test error handling works"
- ❌ NOT "Confirm the API returns 200"
- ❌ NOT checking if code/implementation matches the spec
**FOR requirements quality validation**:
- ✅ "Are visual hierarchy requirements defined for all card types?" (completeness)
- ✅ "Is 'prominent display' quantified with specific sizing/positioning?" (clarity)
- ✅ "Are hover state requirements consistent across all interactive elements?" (consistency)
- ✅ "Are accessibility requirements defined for keyboard navigation?" (coverage)
- ✅ "Does the spec define what happens when logo image fails to load?" (edge cases)
**Metaphor**: If your spec is code written in English, the checklist is its unit test suite. You're testing whether the requirements are well-written, complete, unambiguous, and ready for implementation - NOT whether the implementation works.
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Execution Steps
1. **Setup**: Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json` from repo root and parse JSON for FEATURE_DIR and AVAILABLE_DOCS list.
- All file paths must be absolute.
- For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. **Clarify intent (dynamic)**: Derive up to THREE initial contextual clarifying questions (no pre-baked catalog). They MUST:
- Be generated from the user's phrasing + extracted signals from spec/plan/tasks
- Only ask about information that materially changes checklist content
- Be skipped individually if already unambiguous in `$ARGUMENTS`
- Prefer precision over breadth
Generation algorithm:
1. Extract signals: feature domain keywords (e.g., auth, latency, UX, API), risk indicators ("critical", "must", "compliance"), stakeholder hints ("QA", "review", "security team"), and explicit deliverables ("a11y", "rollback", "contracts").
2. Cluster signals into candidate focus areas (max 4) ranked by relevance.
3. Identify probable audience & timing (author, reviewer, QA, release) if not explicit.
4. Detect missing dimensions: scope breadth, depth/rigor, risk emphasis, exclusion boundaries, measurable acceptance criteria.
5. Formulate questions chosen from these archetypes:
- Scope refinement (e.g., "Should this include integration touchpoints with X and Y or stay limited to local module correctness?")
- Risk prioritization (e.g., "Which of these potential risk areas should receive mandatory gating checks?")
- Depth calibration (e.g., "Is this a lightweight pre-commit sanity list or a formal release gate?")
- Audience framing (e.g., "Will this be used by the author only or peers during PR review?")
- Boundary exclusion (e.g., "Should we explicitly exclude performance tuning items this round?")
- Scenario class gap (e.g., "No recovery flows detected—are rollback / partial failure paths in scope?")
Question formatting rules:
- If presenting options, generate a compact table with columns: Option | Candidate | Why It Matters
- Limit to AE options maximum; omit table if a free-form answer is clearer
- Never ask the user to restate what they already said
- Avoid speculative categories (no hallucination). If uncertain, ask explicitly: "Confirm whether X belongs in scope."
Defaults when interaction impossible:
- Depth: Standard
- Audience: Reviewer (PR) if code-related; Author otherwise
- Focus: Top 2 relevance clusters
Output the questions (label Q1/Q2/Q3). After answers: if ≥2 scenario classes (Alternate / Exception / Recovery / Non-Functional domain) remain unclear, you MAY ask up to TWO more targeted followups (Q4/Q5) with a one-line justification each (e.g., "Unresolved recovery path risk"). Do not exceed five total questions. Skip escalation if user explicitly declines more.
3. **Understand user request**: Combine `$ARGUMENTS` + clarifying answers:
- Derive checklist theme (e.g., security, review, deploy, ux)
- Consolidate explicit must-have items mentioned by user
- Map focus selections to category scaffolding
- Infer any missing context from spec/plan/tasks (do NOT hallucinate)
4. **Load feature context**: Read from FEATURE_DIR:
- spec.md: Feature requirements and scope
- plan.md (if exists): Technical details, dependencies
- tasks.md (if exists): Implementation tasks
**Context Loading Strategy**:
- Load only necessary portions relevant to active focus areas (avoid full-file dumping)
- Prefer summarizing long sections into concise scenario/requirement bullets
- Use progressive disclosure: add follow-on retrieval only if gaps detected
- If source docs are large, generate interim summary items instead of embedding raw text
5. **Generate checklist** - Create "Unit Tests for Requirements":
- Create `FEATURE_DIR/checklists/` directory if it doesn't exist
- Generate unique checklist filename:
- Use short, descriptive name based on domain (e.g., `ux.md`, `api.md`, `security.md`)
- Format: `[domain].md`
- If file exists, append to existing file
- Number items sequentially starting from CHK001
- Each `/speckit.checklist` run creates a NEW file (never overwrites existing checklists)
**CORE PRINCIPLE - Test the Requirements, Not the Implementation**:
Every checklist item MUST evaluate the REQUIREMENTS THEMSELVES for:
- **Completeness**: Are all necessary requirements present?
- **Clarity**: Are requirements unambiguous and specific?
- **Consistency**: Do requirements align with each other?
- **Measurability**: Can requirements be objectively verified?
- **Coverage**: Are all scenarios/edge cases addressed?
**Category Structure** - Group items by requirement quality dimensions:
- **Requirement Completeness** (Are all necessary requirements documented?)
- **Requirement Clarity** (Are requirements specific and unambiguous?)
- **Requirement Consistency** (Do requirements align without conflicts?)
- **Acceptance Criteria Quality** (Are success criteria measurable?)
- **Scenario Coverage** (Are all flows/cases addressed?)
- **Edge Case Coverage** (Are boundary conditions defined?)
- **Non-Functional Requirements** (Performance, Security, Accessibility, etc. - are they specified?)
- **Dependencies & Assumptions** (Are they documented and validated?)
- **Ambiguities & Conflicts** (What needs clarification?)
**HOW TO WRITE CHECKLIST ITEMS - "Unit Tests for English"**:
**WRONG** (Testing implementation):
- "Verify landing page displays 3 episode cards"
- "Test hover states work on desktop"
- "Confirm logo click navigates home"
**CORRECT** (Testing requirements quality):
- "Are the exact number and layout of featured episodes specified?" [Completeness]
- "Is 'prominent display' quantified with specific sizing/positioning?" [Clarity]
- "Are hover state requirements consistent across all interactive elements?" [Consistency]
- "Are keyboard navigation requirements defined for all interactive UI?" [Coverage]
- "Is the fallback behavior specified when logo image fails to load?" [Edge Cases]
- "Are loading states defined for asynchronous episode data?" [Completeness]
- "Does the spec define visual hierarchy for competing UI elements?" [Clarity]
**ITEM STRUCTURE**:
Each item should follow this pattern:
- Question format asking about requirement quality
- Focus on what's WRITTEN (or not written) in the spec/plan
- Include quality dimension in brackets [Completeness/Clarity/Consistency/etc.]
- Reference spec section `[Spec §X.Y]` when checking existing requirements
- Use `[Gap]` marker when checking for missing requirements
**EXAMPLES BY QUALITY DIMENSION**:
Completeness:
- "Are error handling requirements defined for all API failure modes? [Gap]"
- "Are accessibility requirements specified for all interactive elements? [Completeness]"
- "Are mobile breakpoint requirements defined for responsive layouts? [Gap]"
Clarity:
- "Is 'fast loading' quantified with specific timing thresholds? [Clarity, Spec §NFR-2]"
- "Are 'related episodes' selection criteria explicitly defined? [Clarity, Spec §FR-5]"
- "Is 'prominent' defined with measurable visual properties? [Ambiguity, Spec §FR-4]"
Consistency:
- "Do navigation requirements align across all pages? [Consistency, Spec §FR-10]"
- "Are card component requirements consistent between landing and detail pages? [Consistency]"
Coverage:
- "Are requirements defined for zero-state scenarios (no episodes)? [Coverage, Edge Case]"
- "Are concurrent user interaction scenarios addressed? [Coverage, Gap]"
- "Are requirements specified for partial data loading failures? [Coverage, Exception Flow]"
Measurability:
- "Are visual hierarchy requirements measurable/testable? [Acceptance Criteria, Spec §FR-1]"
- "Can 'balanced visual weight' be objectively verified? [Measurability, Spec §FR-2]"
**Scenario Classification & Coverage** (Requirements Quality Focus):
- Check if requirements exist for: Primary, Alternate, Exception/Error, Recovery, Non-Functional scenarios
- For each scenario class, ask: "Are [scenario type] requirements complete, clear, and consistent?"
- If scenario class missing: "Are [scenario type] requirements intentionally excluded or missing? [Gap]"
- Include resilience/rollback when state mutation occurs: "Are rollback requirements defined for migration failures? [Gap]"
**Traceability Requirements**:
- MINIMUM: ≥80% of items MUST include at least one traceability reference
- Each item should reference: spec section `[Spec §X.Y]`, or use markers: `[Gap]`, `[Ambiguity]`, `[Conflict]`, `[Assumption]`
- If no ID system exists: "Is a requirement & acceptance criteria ID scheme established? [Traceability]"
**Surface & Resolve Issues** (Requirements Quality Problems):
Ask questions about the requirements themselves:
- Ambiguities: "Is the term 'fast' quantified with specific metrics? [Ambiguity, Spec §NFR-1]"
- Conflicts: "Do navigation requirements conflict between §FR-10 and §FR-10a? [Conflict]"
- Assumptions: "Is the assumption of 'always available podcast API' validated? [Assumption]"
- Dependencies: "Are external podcast API requirements documented? [Dependency, Gap]"
- Missing definitions: "Is 'visual hierarchy' defined with measurable criteria? [Gap]"
**Content Consolidation**:
- Soft cap: If raw candidate items > 40, prioritize by risk/impact
- Merge near-duplicates checking the same requirement aspect
- If >5 low-impact edge cases, create one item: "Are edge cases X, Y, Z addressed in requirements? [Coverage]"
**🚫 ABSOLUTELY PROHIBITED** - These make it an implementation test, not a requirements test:
- ❌ Any item starting with "Verify", "Test", "Confirm", "Check" + implementation behavior
- ❌ References to code execution, user actions, system behavior
- ❌ "Displays correctly", "works properly", "functions as expected"
- ❌ "Click", "navigate", "render", "load", "execute"
- ❌ Test cases, test plans, QA procedures
- ❌ Implementation details (frameworks, APIs, algorithms)
**✅ REQUIRED PATTERNS** - These test requirements quality:
- ✅ "Are [requirement type] defined/specified/documented for [scenario]?"
- ✅ "Is [vague term] quantified/clarified with specific criteria?"
- ✅ "Are requirements consistent between [section A] and [section B]?"
- ✅ "Can [requirement] be objectively measured/verified?"
- ✅ "Are [edge cases/scenarios] addressed in requirements?"
- ✅ "Does the spec define [missing aspect]?"
6. **Structure Reference**: Generate the checklist following the canonical template in `.specify/templates/checklist-template.md` for title, meta section, category headings, and ID formatting. If template is unavailable, use: H1 title, purpose/created meta lines, `##` category sections containing `- [ ] CHK### <requirement item>` lines with globally incrementing IDs starting at CHK001.
7. **Report**: Output full path to created checklist, item count, and remind user that each run creates a new file. Summarize:
- Focus areas selected
- Depth level
- Actor/timing
- Any explicit user-specified must-have items incorporated
**Important**: Each `/speckit.checklist` command invocation creates a checklist file using short, descriptive names unless file already exists. This allows:
- Multiple checklists of different types (e.g., `ux.md`, `test.md`, `security.md`)
- Simple, memorable filenames that indicate checklist purpose
- Easy identification and navigation in the `checklists/` folder
To avoid clutter, use descriptive types and clean up obsolete checklists when done.
## Example Checklist Types & Sample Items
**UX Requirements Quality:** `ux.md`
Sample items (testing the requirements, NOT the implementation):
- "Are visual hierarchy requirements defined with measurable criteria? [Clarity, Spec §FR-1]"
- "Is the number and positioning of UI elements explicitly specified? [Completeness, Spec §FR-1]"
- "Are interaction state requirements (hover, focus, active) consistently defined? [Consistency]"
- "Are accessibility requirements specified for all interactive elements? [Coverage, Gap]"
- "Is fallback behavior defined when images fail to load? [Edge Case, Gap]"
- "Can 'prominent display' be objectively measured? [Measurability, Spec §FR-4]"
**API Requirements Quality:** `api.md`
Sample items:
- "Are error response formats specified for all failure scenarios? [Completeness]"
- "Are rate limiting requirements quantified with specific thresholds? [Clarity]"
- "Are authentication requirements consistent across all endpoints? [Consistency]"
- "Are retry/timeout requirements defined for external dependencies? [Coverage, Gap]"
- "Is versioning strategy documented in requirements? [Gap]"
**Performance Requirements Quality:** `performance.md`
Sample items:
- "Are performance requirements quantified with specific metrics? [Clarity]"
- "Are performance targets defined for all critical user journeys? [Coverage]"
- "Are performance requirements under different load conditions specified? [Completeness]"
- "Can performance requirements be objectively measured? [Measurability]"
- "Are degradation requirements defined for high-load scenarios? [Edge Case, Gap]"
**Security Requirements Quality:** `security.md`
Sample items:
- "Are authentication requirements specified for all protected resources? [Coverage]"
- "Are data protection requirements defined for sensitive information? [Completeness]"
- "Is the threat model documented and requirements aligned to it? [Traceability]"
- "Are security requirements consistent with compliance obligations? [Consistency]"
- "Are security failure/breach response requirements defined? [Gap, Exception Flow]"
## Anti-Examples: What NOT To Do
**❌ WRONG - These test implementation, not requirements:**
```markdown
- [ ] CHK001 - Verify landing page displays 3 episode cards [Spec §FR-001]
- [ ] CHK002 - Test hover states work correctly on desktop [Spec §FR-003]
- [ ] CHK003 - Confirm logo click navigates to home page [Spec §FR-010]
- [ ] CHK004 - Check that related episodes section shows 3-5 items [Spec §FR-005]
```
**✅ CORRECT - These test requirements quality:**
```markdown
- [ ] CHK001 - Are the number and layout of featured episodes explicitly specified? [Completeness, Spec §FR-001]
- [ ] CHK002 - Are hover state requirements consistently defined for all interactive elements? [Consistency, Spec §FR-003]
- [ ] CHK003 - Are navigation requirements clear for all clickable brand elements? [Clarity, Spec §FR-010]
- [ ] CHK004 - Is the selection criteria for related episodes documented? [Gap, Spec §FR-005]
- [ ] CHK005 - Are loading state requirements defined for asynchronous episode data? [Gap]
- [ ] CHK006 - Can "visual hierarchy" requirements be objectively measured? [Measurability, Spec §FR-001]
```
**Key Differences:**
- Wrong: Tests if the system works correctly
- Correct: Tests if the requirements are written correctly
- Wrong: Verification of behavior
- Correct: Validation of requirement quality
- Wrong: "Does it do X?"
- Correct: "Is X clearly specified?"

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---
description: Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
handoffs:
- label: Build Technical Plan
agent: speckit.plan
prompt: Create a plan for the spec. I am building with...
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
Goal: Detect and reduce ambiguity or missing decision points in the active feature specification and record the clarifications directly in the spec file.
Note: This clarification workflow is expected to run (and be completed) BEFORE invoking `/speckit.plan`. If the user explicitly states they are skipping clarification (e.g., exploratory spike), you may proceed, but must warn that downstream rework risk increases.
Execution steps:
1. Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json -PathsOnly` from repo root **once** (combined `--json --paths-only` mode / `-Json -PathsOnly`). Parse minimal JSON payload fields:
- `FEATURE_DIR`
- `FEATURE_SPEC`
- (Optionally capture `IMPL_PLAN`, `TASKS` for future chained flows.)
- If JSON parsing fails, abort and instruct user to re-run `/speckit.specify` or verify feature branch environment.
- For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. Load the current spec file. Perform a structured ambiguity & coverage scan using this taxonomy. For each category, mark status: Clear / Partial / Missing. Produce an internal coverage map used for prioritization (do not output raw map unless no questions will be asked).
Functional Scope & Behavior:
- Core user goals & success criteria
- Explicit out-of-scope declarations
- User roles / personas differentiation
Domain & Data Model:
- Entities, attributes, relationships
- Identity & uniqueness rules
- Lifecycle/state transitions
- Data volume / scale assumptions
Interaction & UX Flow:
- Critical user journeys / sequences
- Error/empty/loading states
- Accessibility or localization notes
Non-Functional Quality Attributes:
- Performance (latency, throughput targets)
- Scalability (horizontal/vertical, limits)
- Reliability & availability (uptime, recovery expectations)
- Observability (logging, metrics, tracing signals)
- Security & privacy (authN/Z, data protection, threat assumptions)
- Compliance / regulatory constraints (if any)
Integration & External Dependencies:
- External services/APIs and failure modes
- Data import/export formats
- Protocol/versioning assumptions
Edge Cases & Failure Handling:
- Negative scenarios
- Rate limiting / throttling
- Conflict resolution (e.g., concurrent edits)
Constraints & Tradeoffs:
- Technical constraints (language, storage, hosting)
- Explicit tradeoffs or rejected alternatives
Terminology & Consistency:
- Canonical glossary terms
- Avoided synonyms / deprecated terms
Completion Signals:
- Acceptance criteria testability
- Measurable Definition of Done style indicators
Misc / Placeholders:
- TODO markers / unresolved decisions
- Ambiguous adjectives ("robust", "intuitive") lacking quantification
For each category with Partial or Missing status, add a candidate question opportunity unless:
- Clarification would not materially change implementation or validation strategy
- Information is better deferred to planning phase (note internally)
3. Generate (internally) a prioritized queue of candidate clarification questions (maximum 5). Do NOT output them all at once. Apply these constraints:
- Maximum of 10 total questions across the whole session.
- Each question must be answerable with EITHER:
- A short multiplechoice selection (25 distinct, mutually exclusive options), OR
- A one-word / shortphrase answer (explicitly constrain: "Answer in <=5 words").
- Only include questions whose answers materially impact architecture, data modeling, task decomposition, test design, UX behavior, operational readiness, or compliance validation.
- Ensure category coverage balance: attempt to cover the highest impact unresolved categories first; avoid asking two low-impact questions when a single high-impact area (e.g., security posture) is unresolved.
- Exclude questions already answered, trivial stylistic preferences, or plan-level execution details (unless blocking correctness).
- Favor clarifications that reduce downstream rework risk or prevent misaligned acceptance tests.
- If more than 5 categories remain unresolved, select the top 5 by (Impact * Uncertainty) heuristic.
4. Sequential questioning loop (interactive):
- Present EXACTLY ONE question at a time.
- For multiplechoice questions:
- **Analyze all options** and determine the **most suitable option** based on:
- Best practices for the project type
- Common patterns in similar implementations
- Risk reduction (security, performance, maintainability)
- Alignment with any explicit project goals or constraints visible in the spec
- Present your **recommended option prominently** at the top with clear reasoning (1-2 sentences explaining why this is the best choice).
- Format as: `**Recommended:** Option [X] - <reasoning>`
- Then render all options as a Markdown table:
| Option | Description |
|--------|-------------|
| A | <Option A description> |
| B | <Option B description> |
| C | <Option C description> (add D/E as needed up to 5) |
| Short | Provide a different short answer (<=5 words) (Include only if free-form alternative is appropriate) |
- After the table, add: `You can reply with the option letter (e.g., "A"), accept the recommendation by saying "yes" or "recommended", or provide your own short answer.`
- For shortanswer style (no meaningful discrete options):
- Provide your **suggested answer** based on best practices and context.
- Format as: `**Suggested:** <your proposed answer> - <brief reasoning>`
- Then output: `Format: Short answer (<=5 words). You can accept the suggestion by saying "yes" or "suggested", or provide your own answer.`
- After the user answers:
- If the user replies with "yes", "recommended", or "suggested", use your previously stated recommendation/suggestion as the answer.
- Otherwise, validate the answer maps to one option or fits the <=5 word constraint.
- If ambiguous, ask for a quick disambiguation (count still belongs to same question; do not advance).
- Once satisfactory, record it in working memory (do not yet write to disk) and move to the next queued question.
- Stop asking further questions when:
- All critical ambiguities resolved early (remaining queued items become unnecessary), OR
- User signals completion ("done", "good", "no more"), OR
- You reach 5 asked questions.
- Never reveal future queued questions in advance.
- If no valid questions exist at start, immediately report no critical ambiguities.
5. Integration after EACH accepted answer (incremental update approach):
- Maintain in-memory representation of the spec (loaded once at start) plus the raw file contents.
- For the first integrated answer in this session:
- Ensure a `## Clarifications` section exists (create it just after the highest-level contextual/overview section per the spec template if missing).
- Under it, create (if not present) a `### Session YYYY-MM-DD` subheading for today.
- Append a bullet line immediately after acceptance: `- Q: <question> → A: <final answer>`.
- Then immediately apply the clarification to the most appropriate section(s):
- Functional ambiguity → Update or add a bullet in Functional Requirements.
- User interaction / actor distinction → Update User Stories or Actors subsection (if present) with clarified role, constraint, or scenario.
- Data shape / entities → Update Data Model (add fields, types, relationships) preserving ordering; note added constraints succinctly.
- Non-functional constraint → Add/modify measurable criteria in Non-Functional / Quality Attributes section (convert vague adjective to metric or explicit target).
- Edge case / negative flow → Add a new bullet under Edge Cases / Error Handling (or create such subsection if template provides placeholder for it).
- Terminology conflict → Normalize term across spec; retain original only if necessary by adding `(formerly referred to as "X")` once.
- If the clarification invalidates an earlier ambiguous statement, replace that statement instead of duplicating; leave no obsolete contradictory text.
- Save the spec file AFTER each integration to minimize risk of context loss (atomic overwrite).
- Preserve formatting: do not reorder unrelated sections; keep heading hierarchy intact.
- Keep each inserted clarification minimal and testable (avoid narrative drift).
6. Validation (performed after EACH write plus final pass):
- Clarifications session contains exactly one bullet per accepted answer (no duplicates).
- Total asked (accepted) questions ≤ 5.
- Updated sections contain no lingering vague placeholders the new answer was meant to resolve.
- No contradictory earlier statement remains (scan for now-invalid alternative choices removed).
- Markdown structure valid; only allowed new headings: `## Clarifications`, `### Session YYYY-MM-DD`.
- Terminology consistency: same canonical term used across all updated sections.
7. Write the updated spec back to `FEATURE_SPEC`.
8. Report completion (after questioning loop ends or early termination):
- Number of questions asked & answered.
- Path to updated spec.
- Sections touched (list names).
- Coverage summary table listing each taxonomy category with Status: Resolved (was Partial/Missing and addressed), Deferred (exceeds question quota or better suited for planning), Clear (already sufficient), Outstanding (still Partial/Missing but low impact).
- If any Outstanding or Deferred remain, recommend whether to proceed to `/speckit.plan` or run `/speckit.clarify` again later post-plan.
- Suggested next command.
Behavior rules:
- If no meaningful ambiguities found (or all potential questions would be low-impact), respond: "No critical ambiguities detected worth formal clarification." and suggest proceeding.
- If spec file missing, instruct user to run `/speckit.specify` first (do not create a new spec here).
- Never exceed 5 total asked questions (clarification retries for a single question do not count as new questions).
- Avoid speculative tech stack questions unless the absence blocks functional clarity.
- Respect user early termination signals ("stop", "done", "proceed").
- If no questions asked due to full coverage, output a compact coverage summary (all categories Clear) then suggest advancing.
- If quota reached with unresolved high-impact categories remaining, explicitly flag them under Deferred with rationale.
Context for prioritization: $ARGUMENTS

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---
description: Create or update the project constitution from interactive or provided principle inputs, ensuring all dependent templates stay in sync.
handoffs:
- label: Build Specification
agent: speckit.specify
prompt: Implement the feature specification based on the updated constitution. I want to build...
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
You are updating the project constitution at `.specify/memory/constitution.md`. This file is a TEMPLATE containing placeholder tokens in square brackets (e.g. `[PROJECT_NAME]`, `[PRINCIPLE_1_NAME]`). Your job is to (a) collect/derive concrete values, (b) fill the template precisely, and (c) propagate any amendments across dependent artifacts.
**Note**: If `.specify/memory/constitution.md` does not exist yet, it should have been initialized from `.specify/templates/constitution-template.md` during project setup. If it's missing, copy the template first.
Follow this execution flow:
1. Load the existing constitution at `.specify/memory/constitution.md`.
- Identify every placeholder token of the form `[ALL_CAPS_IDENTIFIER]`.
**IMPORTANT**: The user might require less or more principles than the ones used in the template. If a number is specified, respect that - follow the general template. You will update the doc accordingly.
2. Collect/derive values for placeholders:
- If user input (conversation) supplies a value, use it.
- Otherwise infer from existing repo context (README, docs, prior constitution versions if embedded).
- For governance dates: `RATIFICATION_DATE` is the original adoption date (if unknown ask or mark TODO), `LAST_AMENDED_DATE` is today if changes are made, otherwise keep previous.
- `CONSTITUTION_VERSION` must increment according to semantic versioning rules:
- MAJOR: Backward incompatible governance/principle removals or redefinitions.
- MINOR: New principle/section added or materially expanded guidance.
- PATCH: Clarifications, wording, typo fixes, non-semantic refinements.
- If version bump type ambiguous, propose reasoning before finalizing.
3. Draft the updated constitution content:
- Replace every placeholder with concrete text (no bracketed tokens left except intentionally retained template slots that the project has chosen not to define yet—explicitly justify any left).
- Preserve heading hierarchy and comments can be removed once replaced unless they still add clarifying guidance.
- Ensure each Principle section: succinct name line, paragraph (or bullet list) capturing nonnegotiable rules, explicit rationale if not obvious.
- Ensure Governance section lists amendment procedure, versioning policy, and compliance review expectations.
4. Consistency propagation checklist (convert prior checklist into active validations):
- Read `.specify/templates/plan-template.md` and ensure any "Constitution Check" or rules align with updated principles.
- Read `.specify/templates/spec-template.md` for scope/requirements alignment—update if constitution adds/removes mandatory sections or constraints.
- Read `.specify/templates/tasks-template.md` and ensure task categorization reflects new or removed principle-driven task types (e.g., observability, versioning, testing discipline).
- Read each command file in `.specify/templates/commands/*.md` (including this one) to verify no outdated references (agent-specific names like CLAUDE only) remain when generic guidance is required.
- Read any runtime guidance docs (e.g., `README.md`, `docs/quickstart.md`, or agent-specific guidance files if present). Update references to principles changed.
5. Produce a Sync Impact Report (prepend as an HTML comment at top of the constitution file after update):
- Version change: old → new
- List of modified principles (old title → new title if renamed)
- Added sections
- Removed sections
- Templates requiring updates (✅ updated / ⚠ pending) with file paths
- Follow-up TODOs if any placeholders intentionally deferred.
6. Validation before final output:
- No remaining unexplained bracket tokens.
- Version line matches report.
- Dates ISO format YYYY-MM-DD.
- Principles are declarative, testable, and free of vague language ("should" → replace with MUST/SHOULD rationale where appropriate).
7. Write the completed constitution back to `.specify/memory/constitution.md` (overwrite).
8. Output a final summary to the user with:
- New version and bump rationale.
- Any files flagged for manual follow-up.
- Suggested commit message (e.g., `docs: amend constitution to vX.Y.Z (principle additions + governance update)`).
Formatting & Style Requirements:
- Use Markdown headings exactly as in the template (do not demote/promote levels).
- Wrap long rationale lines to keep readability (<100 chars ideally) but do not hard enforce with awkward breaks.
- Keep a single blank line between sections.
- Avoid trailing whitespace.
If the user supplies partial updates (e.g., only one principle revision), still perform validation and version decision steps.
If critical info missing (e.g., ratification date truly unknown), insert `TODO(<FIELD_NAME>): explanation` and include in the Sync Impact Report under deferred items.
Do not create a new template; always operate on the existing `.specify/memory/constitution.md` file.

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---
description: Execute the implementation plan by processing and executing all tasks defined in tasks.md
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json -RequireTasks -IncludeTasks` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. **Check checklists status** (if FEATURE_DIR/checklists/ exists):
- Scan all checklist files in the checklists/ directory
- For each checklist, count:
- Total items: All lines matching `- [ ]` or `- [X]` or `- [x]`
- Completed items: Lines matching `- [X]` or `- [x]`
- Incomplete items: Lines matching `- [ ]`
- Create a status table:
```text
| Checklist | Total | Completed | Incomplete | Status |
|-----------|-------|-----------|------------|--------|
| ux.md | 12 | 12 | 0 | ✓ PASS |
| test.md | 8 | 5 | 3 | ✗ FAIL |
| security.md | 6 | 6 | 0 | ✓ PASS |
```
- Calculate overall status:
- **PASS**: All checklists have 0 incomplete items
- **FAIL**: One or more checklists have incomplete items
- **If any checklist is incomplete**:
- Display the table with incomplete item counts
- **STOP** and ask: "Some checklists are incomplete. Do you want to proceed with implementation anyway? (yes/no)"
- Wait for user response before continuing
- If user says "no" or "wait" or "stop", halt execution
- If user says "yes" or "proceed" or "continue", proceed to step 3
- **If all checklists are complete**:
- Display the table showing all checklists passed
- Automatically proceed to step 3
3. Load and analyze the implementation context:
- **REQUIRED**: Read tasks.md for the complete task list and execution plan
- **REQUIRED**: Read plan.md for tech stack, architecture, and file structure
- **IF EXISTS**: Read data-model.md for entities and relationships
- **IF EXISTS**: Read contracts/ for API specifications and test requirements
- **IF EXISTS**: Read research.md for technical decisions and constraints
- **IF EXISTS**: Read quickstart.md for integration scenarios
4. **Project Setup Verification**:
- **REQUIRED**: Create/verify ignore files based on actual project setup:
**Detection & Creation Logic**:
- Check if the following command succeeds to determine if the repository is a git repo (create/verify .gitignore if so):
```sh
git rev-parse --git-dir 2>/dev/null
```
- Check if Dockerfile* exists or Docker in plan.md → create/verify .dockerignore
- Check if .eslintrc* exists → create/verify .eslintignore
- Check if eslint.config.* exists → ensure the config's `ignores` entries cover required patterns
- Check if .prettierrc* exists → create/verify .prettierignore
- Check if .npmrc or package.json exists → create/verify .npmignore (if publishing)
- Check if terraform files (*.tf) exist → create/verify .terraformignore
- Check if .helmignore needed (helm charts present) → create/verify .helmignore
**If ignore file already exists**: Verify it contains essential patterns, append missing critical patterns only
**If ignore file missing**: Create with full pattern set for detected technology
**Common Patterns by Technology** (from plan.md tech stack):
- **Node.js/JavaScript/TypeScript**: `node_modules/`, `dist/`, `build/`, `*.log`, `.env*`
- **Python**: `__pycache__/`, `*.pyc`, `.venv/`, `venv/`, `dist/`, `*.egg-info/`
- **Java**: `target/`, `*.class`, `*.jar`, `.gradle/`, `build/`
- **C#/.NET**: `bin/`, `obj/`, `*.user`, `*.suo`, `packages/`
- **Go**: `*.exe`, `*.test`, `vendor/`, `*.out`
- **Ruby**: `.bundle/`, `log/`, `tmp/`, `*.gem`, `vendor/bundle/`
- **PHP**: `vendor/`, `*.log`, `*.cache`, `*.env`
- **Rust**: `target/`, `debug/`, `release/`, `*.rs.bk`, `*.rlib`, `*.prof*`, `.idea/`, `*.log`, `.env*`
- **Kotlin**: `build/`, `out/`, `.gradle/`, `.idea/`, `*.class`, `*.jar`, `*.iml`, `*.log`, `.env*`
- **C++**: `build/`, `bin/`, `obj/`, `out/`, `*.o`, `*.so`, `*.a`, `*.exe`, `*.dll`, `.idea/`, `*.log`, `.env*`
- **C**: `build/`, `bin/`, `obj/`, `out/`, `*.o`, `*.a`, `*.so`, `*.exe`, `Makefile`, `config.log`, `.idea/`, `*.log`, `.env*`
- **Swift**: `.build/`, `DerivedData/`, `*.swiftpm/`, `Packages/`
- **R**: `.Rproj.user/`, `.Rhistory`, `.RData`, `.Ruserdata`, `*.Rproj`, `packrat/`, `renv/`
- **Universal**: `.DS_Store`, `Thumbs.db`, `*.tmp`, `*.swp`, `.vscode/`, `.idea/`
**Tool-Specific Patterns**:
- **Docker**: `node_modules/`, `.git/`, `Dockerfile*`, `.dockerignore`, `*.log*`, `.env*`, `coverage/`
- **ESLint**: `node_modules/`, `dist/`, `build/`, `coverage/`, `*.min.js`
- **Prettier**: `node_modules/`, `dist/`, `build/`, `coverage/`, `package-lock.json`, `yarn.lock`, `pnpm-lock.yaml`
- **Terraform**: `.terraform/`, `*.tfstate*`, `*.tfvars`, `.terraform.lock.hcl`
- **Kubernetes/k8s**: `*.secret.yaml`, `secrets/`, `.kube/`, `kubeconfig*`, `*.key`, `*.crt`
5. Parse tasks.md structure and extract:
- **Task phases**: Setup, Tests, Core, Integration, Polish
- **Task dependencies**: Sequential vs parallel execution rules
- **Task details**: ID, description, file paths, parallel markers [P]
- **Execution flow**: Order and dependency requirements
6. Execute implementation following the task plan:
- **Phase-by-phase execution**: Complete each phase before moving to the next
- **Respect dependencies**: Run sequential tasks in order, parallel tasks [P] can run together
- **Follow TDD approach**: Execute test tasks before their corresponding implementation tasks
- **File-based coordination**: Tasks affecting the same files must run sequentially
- **Validation checkpoints**: Verify each phase completion before proceeding
7. Implementation execution rules:
- **Setup first**: Initialize project structure, dependencies, configuration
- **Tests before code**: If you need to write tests for contracts, entities, and integration scenarios
- **Core development**: Implement models, services, CLI commands, endpoints
- **Integration work**: Database connections, middleware, logging, external services
- **Polish and validation**: Unit tests, performance optimization, documentation
8. Progress tracking and error handling:
- Report progress after each completed task
- Halt execution if any non-parallel task fails
- For parallel tasks [P], continue with successful tasks, report failed ones
- Provide clear error messages with context for debugging
- Suggest next steps if implementation cannot proceed
- **IMPORTANT** For completed tasks, make sure to mark the task off as [X] in the tasks file.
9. Completion validation:
- Verify all required tasks are completed
- Check that implemented features match the original specification
- Validate that tests pass and coverage meets requirements
- Confirm the implementation follows the technical plan
- Report final status with summary of completed work
Note: This command assumes a complete task breakdown exists in tasks.md. If tasks are incomplete or missing, suggest running `/speckit.tasks` first to regenerate the task list.

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---
description: Execute the implementation planning workflow using the plan template to generate design artifacts.
handoffs:
- label: Create Tasks
agent: speckit.tasks
prompt: Break the plan into tasks
send: true
- label: Create Checklist
agent: speckit.checklist
prompt: Create a checklist for the following domain...
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. **Setup**: Run `.specify/scripts/powershell/setup-plan.ps1 -Json` from repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. **Load context**: Read FEATURE_SPEC and `.specify/memory/constitution.md`. Load IMPL_PLAN template (already copied).
3. **Execute plan workflow**: Follow the structure in IMPL_PLAN template to:
- Fill Technical Context (mark unknowns as "NEEDS CLARIFICATION")
- Fill Constitution Check section from constitution
- Evaluate gates (ERROR if violations unjustified)
- Phase 0: Generate research.md (resolve all NEEDS CLARIFICATION)
- Phase 1: Generate data-model.md, contracts/, quickstart.md
- Phase 1: Update agent context by running the agent script
- Re-evaluate Constitution Check post-design
4. **Stop and report**: Command ends after Phase 2 planning. Report branch, IMPL_PLAN path, and generated artifacts.
## Phases
### Phase 0: Outline & Research
1. **Extract unknowns from Technical Context** above:
- For each NEEDS CLARIFICATION → research task
- For each dependency → best practices task
- For each integration → patterns task
2. **Generate and dispatch research agents**:
```text
For each unknown in Technical Context:
Task: "Research {unknown} for {feature context}"
For each technology choice:
Task: "Find best practices for {tech} in {domain}"
```
3. **Consolidate findings** in `research.md` using format:
- Decision: [what was chosen]
- Rationale: [why chosen]
- Alternatives considered: [what else evaluated]
**Output**: research.md with all NEEDS CLARIFICATION resolved
### Phase 1: Design & Contracts
**Prerequisites:** `research.md` complete
1. **Extract entities from feature spec** → `data-model.md`:
- Entity name, fields, relationships
- Validation rules from requirements
- State transitions if applicable
2. **Define interface contracts** (if project has external interfaces) → `/contracts/`:
- Identify what interfaces the project exposes to users or other systems
- Document the contract format appropriate for the project type
- Examples: public APIs for libraries, command schemas for CLI tools, endpoints for web services, grammars for parsers, UI contracts for applications
- Skip if project is purely internal (build scripts, one-off tools, etc.)
3. **Agent context update**:
- Run `.specify/scripts/powershell/update-agent-context.ps1 -AgentType claude`
- These scripts detect which AI agent is in use
- Update the appropriate agent-specific context file
- Add only new technology from current plan
- Preserve manual additions between markers
**Output**: data-model.md, /contracts/*, quickstart.md, agent-specific file
## Key rules
- Use absolute paths
- ERROR on gate failures or unresolved clarifications

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---
description: Create or update the feature specification from a natural language feature description.
handoffs:
- label: Build Technical Plan
agent: speckit.plan
prompt: Create a plan for the spec. I am building with...
- label: Clarify Spec Requirements
agent: speckit.clarify
prompt: Clarify specification requirements
send: true
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
The text the user typed after `/speckit.specify` in the triggering message **is** the feature description. Assume you always have it available in this conversation even if `$ARGUMENTS` appears literally below. Do not ask the user to repeat it unless they provided an empty command.
Given that feature description, do this:
1. **Generate a concise short name** (2-4 words) for the branch:
- Analyze the feature description and extract the most meaningful keywords
- Create a 2-4 word short name that captures the essence of the feature
- Use action-noun format when possible (e.g., "add-user-auth", "fix-payment-bug")
- Preserve technical terms and acronyms (OAuth2, API, JWT, etc.)
- Keep it concise but descriptive enough to understand the feature at a glance
- Examples:
- "I want to add user authentication" → "user-auth"
- "Implement OAuth2 integration for the API" → "oauth2-api-integration"
- "Create a dashboard for analytics" → "analytics-dashboard"
- "Fix payment processing timeout bug" → "fix-payment-timeout"
2. **Check for existing branches before creating new one**:
a. First, fetch all remote branches to ensure we have the latest information:
```bash
git fetch --all --prune
```
b. Find the highest feature number across all sources for the short-name:
- Remote branches: `git ls-remote --heads origin | grep -E 'refs/heads/[0-9]+-<short-name>$'`
- Local branches: `git branch | grep -E '^[* ]*[0-9]+-<short-name>$'`
- Specs directories: Check for directories matching `specs/[0-9]+-<short-name>`
c. Determine the next available number:
- Extract all numbers from all three sources
- Find the highest number N
- Use N+1 for the new branch number
d. Run the script `.specify/scripts/powershell/create-new-feature.ps1 -Json "$ARGUMENTS"` with the calculated number and short-name:
- Pass `--number N+1` and `--short-name "your-short-name"` along with the feature description
- Bash example: `.specify/scripts/powershell/create-new-feature.ps1 -Json "$ARGUMENTS" --json --number 5 --short-name "user-auth" "Add user authentication"`
- PowerShell example: `.specify/scripts/powershell/create-new-feature.ps1 -Json "$ARGUMENTS" -Json -Number 5 -ShortName "user-auth" "Add user authentication"`
**IMPORTANT**:
- Check all three sources (remote branches, local branches, specs directories) to find the highest number
- Only match branches/directories with the exact short-name pattern
- If no existing branches/directories found with this short-name, start with number 1
- You must only ever run this script once per feature
- The JSON is provided in the terminal as output - always refer to it to get the actual content you're looking for
- The JSON output will contain BRANCH_NAME and SPEC_FILE paths
- For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot")
3. Load `.specify/templates/spec-template.md` to understand required sections.
4. Follow this execution flow:
1. Parse user description from Input
If empty: ERROR "No feature description provided"
2. Extract key concepts from description
Identify: actors, actions, data, constraints
3. For unclear aspects:
- Make informed guesses based on context and industry standards
- Only mark with [NEEDS CLARIFICATION: specific question] if:
- The choice significantly impacts feature scope or user experience
- Multiple reasonable interpretations exist with different implications
- No reasonable default exists
- **LIMIT: Maximum 3 [NEEDS CLARIFICATION] markers total**
- Prioritize clarifications by impact: scope > security/privacy > user experience > technical details
4. Fill User Scenarios & Testing section
If no clear user flow: ERROR "Cannot determine user scenarios"
5. Generate Functional Requirements
Each requirement must be testable
Use reasonable defaults for unspecified details (document assumptions in Assumptions section)
6. Define Success Criteria
Create measurable, technology-agnostic outcomes
Include both quantitative metrics (time, performance, volume) and qualitative measures (user satisfaction, task completion)
Each criterion must be verifiable without implementation details
7. Identify Key Entities (if data involved)
8. Return: SUCCESS (spec ready for planning)
5. Write the specification to SPEC_FILE using the template structure, replacing placeholders with concrete details derived from the feature description (arguments) while preserving section order and headings.
6. **Specification Quality Validation**: After writing the initial spec, validate it against quality criteria:
a. **Create Spec Quality Checklist**: Generate a checklist file at `FEATURE_DIR/checklists/requirements.md` using the checklist template structure with these validation items:
```markdown
# Specification Quality Checklist: [FEATURE NAME]
**Purpose**: Validate specification completeness and quality before proceeding to planning
**Created**: [DATE]
**Feature**: [Link to spec.md]
## Content Quality
- [ ] No implementation details (languages, frameworks, APIs)
- [ ] Focused on user value and business needs
- [ ] Written for non-technical stakeholders
- [ ] All mandatory sections completed
## Requirement Completeness
- [ ] No [NEEDS CLARIFICATION] markers remain
- [ ] Requirements are testable and unambiguous
- [ ] Success criteria are measurable
- [ ] Success criteria are technology-agnostic (no implementation details)
- [ ] All acceptance scenarios are defined
- [ ] Edge cases are identified
- [ ] Scope is clearly bounded
- [ ] Dependencies and assumptions identified
## Feature Readiness
- [ ] All functional requirements have clear acceptance criteria
- [ ] User scenarios cover primary flows
- [ ] Feature meets measurable outcomes defined in Success Criteria
- [ ] No implementation details leak into specification
## Notes
- Items marked incomplete require spec updates before `/speckit.clarify` or `/speckit.plan`
```
b. **Run Validation Check**: Review the spec against each checklist item:
- For each item, determine if it passes or fails
- Document specific issues found (quote relevant spec sections)
c. **Handle Validation Results**:
- **If all items pass**: Mark checklist complete and proceed to step 6
- **If items fail (excluding [NEEDS CLARIFICATION])**:
1. List the failing items and specific issues
2. Update the spec to address each issue
3. Re-run validation until all items pass (max 3 iterations)
4. If still failing after 3 iterations, document remaining issues in checklist notes and warn user
- **If [NEEDS CLARIFICATION] markers remain**:
1. Extract all [NEEDS CLARIFICATION: ...] markers from the spec
2. **LIMIT CHECK**: If more than 3 markers exist, keep only the 3 most critical (by scope/security/UX impact) and make informed guesses for the rest
3. For each clarification needed (max 3), present options to user in this format:
```markdown
## Question [N]: [Topic]
**Context**: [Quote relevant spec section]
**What we need to know**: [Specific question from NEEDS CLARIFICATION marker]
**Suggested Answers**:
| Option | Answer | Implications |
|--------|--------|--------------|
| A | [First suggested answer] | [What this means for the feature] |
| B | [Second suggested answer] | [What this means for the feature] |
| C | [Third suggested answer] | [What this means for the feature] |
| Custom | Provide your own answer | [Explain how to provide custom input] |
**Your choice**: _[Wait for user response]_
```
4. **CRITICAL - Table Formatting**: Ensure markdown tables are properly formatted:
- Use consistent spacing with pipes aligned
- Each cell should have spaces around content: `| Content |` not `|Content|`
- Header separator must have at least 3 dashes: `|--------|`
- Test that the table renders correctly in markdown preview
5. Number questions sequentially (Q1, Q2, Q3 - max 3 total)
6. Present all questions together before waiting for responses
7. Wait for user to respond with their choices for all questions (e.g., "Q1: A, Q2: Custom - [details], Q3: B")
8. Update the spec by replacing each [NEEDS CLARIFICATION] marker with the user's selected or provided answer
9. Re-run validation after all clarifications are resolved
d. **Update Checklist**: After each validation iteration, update the checklist file with current pass/fail status
7. Report completion with branch name, spec file path, checklist results, and readiness for the next phase (`/speckit.clarify` or `/speckit.plan`).
**NOTE:** The script creates and checks out the new branch and initializes the spec file before writing.
## General Guidelines
## Quick Guidelines
- Focus on **WHAT** users need and **WHY**.
- Avoid HOW to implement (no tech stack, APIs, code structure).
- Written for business stakeholders, not developers.
- DO NOT create any checklists that are embedded in the spec. That will be a separate command.
### Section Requirements
- **Mandatory sections**: Must be completed for every feature
- **Optional sections**: Include only when relevant to the feature
- When a section doesn't apply, remove it entirely (don't leave as "N/A")
### For AI Generation
When creating this spec from a user prompt:
1. **Make informed guesses**: Use context, industry standards, and common patterns to fill gaps
2. **Document assumptions**: Record reasonable defaults in the Assumptions section
3. **Limit clarifications**: Maximum 3 [NEEDS CLARIFICATION] markers - use only for critical decisions that:
- Significantly impact feature scope or user experience
- Have multiple reasonable interpretations with different implications
- Lack any reasonable default
4. **Prioritize clarifications**: scope > security/privacy > user experience > technical details
5. **Think like a tester**: Every vague requirement should fail the "testable and unambiguous" checklist item
6. **Common areas needing clarification** (only if no reasonable default exists):
- Feature scope and boundaries (include/exclude specific use cases)
- User types and permissions (if multiple conflicting interpretations possible)
- Security/compliance requirements (when legally/financially significant)
**Examples of reasonable defaults** (don't ask about these):
- Data retention: Industry-standard practices for the domain
- Performance targets: Standard web/mobile app expectations unless specified
- Error handling: User-friendly messages with appropriate fallbacks
- Authentication method: Standard session-based or OAuth2 for web apps
- Integration patterns: Use project-appropriate patterns (REST/GraphQL for web services, function calls for libraries, CLI args for tools, etc.)
### Success Criteria Guidelines
Success criteria must be:
1. **Measurable**: Include specific metrics (time, percentage, count, rate)
2. **Technology-agnostic**: No mention of frameworks, languages, databases, or tools
3. **User-focused**: Describe outcomes from user/business perspective, not system internals
4. **Verifiable**: Can be tested/validated without knowing implementation details
**Good examples**:
- "Users can complete checkout in under 3 minutes"
- "System supports 10,000 concurrent users"
- "95% of searches return results in under 1 second"
- "Task completion rate improves by 40%"
**Bad examples** (implementation-focused):
- "API response time is under 200ms" (too technical, use "Users see results instantly")
- "Database can handle 1000 TPS" (implementation detail, use user-facing metric)
- "React components render efficiently" (framework-specific)
- "Redis cache hit rate above 80%" (technology-specific)

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@@ -0,0 +1,137 @@
---
description: Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.
handoffs:
- label: Analyze For Consistency
agent: speckit.analyze
prompt: Run a project analysis for consistency
send: true
- label: Implement Project
agent: speckit.implement
prompt: Start the implementation in phases
send: true
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. **Setup**: Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
2. **Load design documents**: Read from FEATURE_DIR:
- **Required**: plan.md (tech stack, libraries, structure), spec.md (user stories with priorities)
- **Optional**: data-model.md (entities), contracts/ (interface contracts), research.md (decisions), quickstart.md (test scenarios)
- Note: Not all projects have all documents. Generate tasks based on what's available.
3. **Execute task generation workflow**:
- Load plan.md and extract tech stack, libraries, project structure
- Load spec.md and extract user stories with their priorities (P1, P2, P3, etc.)
- If data-model.md exists: Extract entities and map to user stories
- If contracts/ exists: Map interface contracts to user stories
- If research.md exists: Extract decisions for setup tasks
- Generate tasks organized by user story (see Task Generation Rules below)
- Generate dependency graph showing user story completion order
- Create parallel execution examples per user story
- Validate task completeness (each user story has all needed tasks, independently testable)
4. **Generate tasks.md**: Use `.specify/templates/tasks-template.md` as structure, fill with:
- Correct feature name from plan.md
- Phase 1: Setup tasks (project initialization)
- Phase 2: Foundational tasks (blocking prerequisites for all user stories)
- Phase 3+: One phase per user story (in priority order from spec.md)
- Each phase includes: story goal, independent test criteria, tests (if requested), implementation tasks
- Final Phase: Polish & cross-cutting concerns
- All tasks must follow the strict checklist format (see Task Generation Rules below)
- Clear file paths for each task
- Dependencies section showing story completion order
- Parallel execution examples per story
- Implementation strategy section (MVP first, incremental delivery)
5. **Report**: Output path to generated tasks.md and summary:
- Total task count
- Task count per user story
- Parallel opportunities identified
- Independent test criteria for each story
- Suggested MVP scope (typically just User Story 1)
- Format validation: Confirm ALL tasks follow the checklist format (checkbox, ID, labels, file paths)
Context for task generation: $ARGUMENTS
The tasks.md should be immediately executable - each task must be specific enough that an LLM can complete it without additional context.
## Task Generation Rules
**CRITICAL**: Tasks MUST be organized by user story to enable independent implementation and testing.
**Tests are OPTIONAL**: Only generate test tasks if explicitly requested in the feature specification or if user requests TDD approach.
### Checklist Format (REQUIRED)
Every task MUST strictly follow this format:
```text
- [ ] [TaskID] [P?] [Story?] Description with file path
```
**Format Components**:
1. **Checkbox**: ALWAYS start with `- [ ]` (markdown checkbox)
2. **Task ID**: Sequential number (T001, T002, T003...) in execution order
3. **[P] marker**: Include ONLY if task is parallelizable (different files, no dependencies on incomplete tasks)
4. **[Story] label**: REQUIRED for user story phase tasks only
- Format: [US1], [US2], [US3], etc. (maps to user stories from spec.md)
- Setup phase: NO story label
- Foundational phase: NO story label
- User Story phases: MUST have story label
- Polish phase: NO story label
5. **Description**: Clear action with exact file path
**Examples**:
- ✅ CORRECT: `- [ ] T001 Create project structure per implementation plan`
- ✅ CORRECT: `- [ ] T005 [P] Implement authentication middleware in src/middleware/auth.py`
- ✅ CORRECT: `- [ ] T012 [P] [US1] Create User model in src/models/user.py`
- ✅ CORRECT: `- [ ] T014 [US1] Implement UserService in src/services/user_service.py`
- ❌ WRONG: `- [ ] Create User model` (missing ID and Story label)
- ❌ WRONG: `T001 [US1] Create model` (missing checkbox)
- ❌ WRONG: `- [ ] [US1] Create User model` (missing Task ID)
- ❌ WRONG: `- [ ] T001 [US1] Create model` (missing file path)
### Task Organization
1. **From User Stories (spec.md)** - PRIMARY ORGANIZATION:
- Each user story (P1, P2, P3...) gets its own phase
- Map all related components to their story:
- Models needed for that story
- Services needed for that story
- Interfaces/UI needed for that story
- If tests requested: Tests specific to that story
- Mark story dependencies (most stories should be independent)
2. **From Contracts**:
- Map each interface contract → to the user story it serves
- If tests requested: Each interface contract → contract test task [P] before implementation in that story's phase
3. **From Data Model**:
- Map each entity to the user story(ies) that need it
- If entity serves multiple stories: Put in earliest story or Setup phase
- Relationships → service layer tasks in appropriate story phase
4. **From Setup/Infrastructure**:
- Shared infrastructure → Setup phase (Phase 1)
- Foundational/blocking tasks → Foundational phase (Phase 2)
- Story-specific setup → within that story's phase
### Phase Structure
- **Phase 1**: Setup (project initialization)
- **Phase 2**: Foundational (blocking prerequisites - MUST complete before user stories)
- **Phase 3+**: User Stories in priority order (P1, P2, P3...)
- Within each story: Tests (if requested) → Models → Services → Endpoints → Integration
- Each phase should be a complete, independently testable increment
- **Final Phase**: Polish & Cross-Cutting Concerns

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@@ -0,0 +1,30 @@
---
description: Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.
tools: ['github/github-mcp-server/issue_write']
---
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json -RequireTasks -IncludeTasks` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
1. From the executed script, extract the path to **tasks**.
1. Get the Git remote by running:
```bash
git config --get remote.origin.url
```
> [!CAUTION]
> ONLY PROCEED TO NEXT STEPS IF THE REMOTE IS A GITHUB URL
1. For each task in the list, use the GitHub MCP server to create a new issue in the repository that is representative of the Git remote.
> [!CAUTION]
> UNDER NO CIRCUMSTANCES EVER CREATE ISSUES IN REPOSITORIES THAT DO NOT MATCH THE REMOTE URL

85
.env.example Normal file
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@@ -0,0 +1,85 @@
# ImageApi configuration template. Copy to `.env` and fill in for your
# deploy. Comments mirror the canonical docs in CLAUDE.md — see there
# for the full picture (especially the AI-Insights / Apollo / face
# integration sections).
# ── Required ────────────────────────────────────────────────────────────
DATABASE_URL=./database.db
BASE_PATH=/path/to/media
THUMBNAILS=/path/to/thumbnails
VIDEO_PATH=/path/to/video/hls
GIFS_DIRECTORY=/path/to/gifs
PREVIEW_CLIPS_DIRECTORY=/path/to/preview-clips
BIND_URL=0.0.0.0:8080
CORS_ALLOWED_ORIGINS=http://localhost:3000
SECRET_KEY=replace-me-with-a-long-random-secret
RUST_LOG=info
# ── File watching ───────────────────────────────────────────────────────
# Quick scan = recently-modified-files only; full scan = comprehensive walk.
WATCH_QUICK_INTERVAL_SECONDS=60
WATCH_FULL_INTERVAL_SECONDS=3600
# Comma-separated path prefixes / component names to skip in /memories
# AND in face detection (e.g. @eaDir, .thumbnails, /private).
EXCLUDED_DIRS=
# ── Video / HLS ─────────────────────────────────────────────────────────
HLS_CONCURRENCY=2
HLS_TIMEOUT_SECONDS=900
PLAYLIST_CLEANUP_INTERVAL_SECONDS=86400
# ── Telemetry (release builds only) ─────────────────────────────────────
# OTLP_OTLS_ENDPOINT=http://localhost:4317
# ── AI Insights — Ollama (local LLM) ────────────────────────────────────
OLLAMA_PRIMARY_URL=http://localhost:11434
OLLAMA_PRIMARY_MODEL=nemotron-3-nano:30b
# Optional fallback server tried on connection failure.
# OLLAMA_FALLBACK_URL=http://server:11434
# OLLAMA_FALLBACK_MODEL=llama3.2:3b
OLLAMA_REQUEST_TIMEOUT_SECONDS=120
# Cap on tool-calling iterations per chat turn / agentic insight.
AGENTIC_MAX_ITERATIONS=6
AGENTIC_CHAT_MAX_ITERATIONS=6
# ── AI Insights — OpenRouter (hybrid backend, optional) ─────────────────
# Set OPENROUTER_API_KEY to enable the hybrid backend (vision stays
# local on Ollama, chat routes to OpenRouter).
# OPENROUTER_API_KEY=sk-or-...
# OPENROUTER_DEFAULT_MODEL=anthropic/claude-sonnet-4
# OPENROUTER_ALLOWED_MODELS=openai/gpt-4o-mini,anthropic/claude-haiku-4-5,google/gemini-2.5-flash
# OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
# OPENROUTER_EMBEDDING_MODEL=openai/text-embedding-3-small
# OPENROUTER_HTTP_REFERER=https://your-site.example
# OPENROUTER_APP_TITLE=ImageApi
# ── AI Insights — sibling services (optional) ───────────────────────────
# Apollo (places + face inference). Single Apollo deploys typically set
# only APOLLO_API_BASE_URL and let the face client fall back to it.
# APOLLO_API_BASE_URL=http://apollo.lan:8000
# APOLLO_FACE_API_BASE_URL=http://apollo.lan:8000
# SMS_API_URL=http://localhost:8000
# SMS_API_TOKEN=
# Display name used in agentic prompts when the LLM refers to "you".
USER_NAME=
# ── Face detection (Phase 3+) ───────────────────────────────────────────
# Cosine-sim floor for auto-binding a detected face to an existing
# same-named person on detection. 0.4 ≈ moderate-confidence match.
FACE_AUTOBIND_MIN_COS=0.4
# Per-scan-tick fan-out into Apollo's detect endpoint. Apollo's GPU
# pool serializes server-side; this just overlaps file-IO with
# inference RTT.
FACE_DETECT_CONCURRENCY=8
# Per-detect HTTP timeout. CPU-only Apollo deploys may need higher.
FACE_DETECT_TIMEOUT_SEC=60
# Per-tick caps on the two backlog drains (independent of WATCH_*
# quick / full scans). Tune up if you have a large unscanned backlog
# and want it to clear faster; tune down if Apollo is overloaded.
FACE_BACKLOG_MAX_PER_TICK=64
FACE_HASH_BACKFILL_MAX_PER_TICK=2000
# ── RAG / search ────────────────────────────────────────────────────────
# Set to `1` to enable cross-encoder reranking on /search results.
SEARCH_RAG_RERANK=0

9
.gitignore vendored
View File

@@ -1,13 +1,22 @@
/target
database/target
*.db
*.db.bak
*.db-shm
*.db-wal
.env
/tmp
/docs
/specs
# Default ignored files
.idea/shelf/
.idea/workspace.xml
.idea/inspectionProfiles/
.idea/markdown.xml
# Datasource local storage ignored files
.idea/dataSources*
.idea/dataSources.local.xml
# Editor-based HTTP Client requests
.idea/httpRequests/
/.claude/settings.local.json

1
.idea/image-api.iml generated
View File

@@ -3,6 +3,7 @@
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$">
<sourceFolder url="file://$MODULE_DIR$/src" isTestSource="false" />
<excludeFolder url="file://$MODULE_DIR$/.idea/dataSources" />
<excludeFolder url="file://$MODULE_DIR$/target" />
</content>
<orderEntry type="inheritedJdk" />

View File

@@ -0,0 +1,149 @@
<!--
Sync Impact Report
==================
Version change: (new) -> 1.0.0
Modified principles: N/A (initial ratification)
Added sections:
- Core Principles (5 principles)
- Technology Stack & Constraints
- Development Workflow
- Governance
Removed sections: N/A
Templates requiring updates:
- .specify/templates/plan-template.md — ✅ no changes needed (Constitution Check section is generic)
- .specify/templates/spec-template.md — ✅ no changes needed
- .specify/templates/tasks-template.md — ✅ no changes needed
- .specify/templates/checklist-template.md — ✅ no changes needed
- .specify/templates/agent-file-template.md — ✅ no changes needed
Follow-up TODOs: None
-->
# ImageApi Constitution
## Core Principles
### I. Layered Architecture
All features MUST follow the established layered architecture:
- **HTTP Layer** (`main.rs`, feature modules): Route handlers, request
parsing, response formatting. No direct database access.
- **Service Layer** (`files.rs`, `exif.rs`, `memories.rs`, etc.): Business
logic. No HTTP-specific types.
- **DAO Layer** (`database/` trait definitions): Trait-based data access
contracts. Every DAO MUST be defined as a trait to enable mock
implementations for testing.
- **Database Layer** (Diesel ORM, `schema.rs`): Concrete `Sqlite*Dao`
implementations. All queries traced with OpenTelemetry.
New features MUST NOT bypass layers (e.g., HTTP handlers MUST NOT
execute raw SQL). Actix actors are permitted for long-running async
work (video processing, file watching) but MUST interact with the
DAO layer through the established trait interfaces.
### II. Path Safety (NON-NEGOTIABLE)
All user-supplied file paths MUST be validated against `BASE_PATH`
using `is_valid_full_path()` before any filesystem operation. This
prevents directory traversal attacks.
- Paths stored in the database MUST be relative to `BASE_PATH`.
- Paths passed to external tools (ffmpeg, image processing) MUST be
fully resolved absolute paths.
- Extension detection MUST use the centralized helpers in
`file_types.rs` (case-insensitive). Manual string matching on
extensions is prohibited.
### III. Trait-Based Testability
All data access MUST go through trait-based DAOs so that every
handler and service can be tested with mock implementations.
- Each DAO trait MUST be defined in `src/database/` and require
`Sync + Send`.
- Mock DAOs for testing MUST live in `src/testhelpers.rs`.
- Integration tests against real SQLite MUST use in-memory databases
via `in_memory_db_connection()` from `database::test`.
- Handler tests MUST use `actix_web::test` utilities with JWT token
injection (using `Claims::valid_user()` and the `test_key` secret).
- New DAO implementations MUST include a `#[cfg(test)]` constructor
(e.g., `from_connection`) accepting an injected connection.
### IV. Environment-Driven Configuration
Server behavior MUST be controlled through environment variables
loaded from `.env` files. Hard-coded paths, URLs, or secrets are
prohibited.
- Required variables MUST call `.expect()` with a clear message at
startup so misconfiguration fails fast.
- Optional variables MUST use `.unwrap_or_else()` with sensible
defaults and be documented in `README.md`.
- Any new environment variable MUST be added to the README
environment section before the feature is considered complete.
### V. Observability
All database operations and HTTP handlers MUST be instrumented
with OpenTelemetry spans via the `trace_db_call` helper or
equivalent tracing macros.
- Release builds export traces to the configured OTLP endpoint.
- Debug builds use the basic logger.
- Prometheus metrics (`imageserver_image_total`,
`imageserver_video_total`) MUST be maintained for key counters.
- Errors MUST be logged at `error!` level with sufficient context
for debugging without reproducing the issue.
## Technology Stack & Constraints
- **Language**: Rust (stable toolchain, Cargo build system)
- **HTTP Framework**: Actix-web 4
- **ORM**: Diesel 2.2 with SQLite backend
- **Auth**: JWT (HS256) via `jsonwebtoken` crate, bcrypt password
hashing
- **Video Processing**: ffmpeg/ffprobe (CLI, must be on PATH)
- **Image Processing**: `image` crate for thumbnails, `kamadak-exif`
for EXIF extraction
- **Tracing**: OpenTelemetry with OTLP export (release),
basic logger (debug)
- **Testing**: `cargo test`, `actix_web::test`, in-memory SQLite
External dependencies (ffmpeg, Ollama) are optional runtime
requirements. The server MUST start and serve core functionality
(images, thumbnails, tags) without them. Features that depend on
optional services MUST degrade gracefully with logged warnings,
not panics.
## Development Workflow
- `cargo fmt` MUST pass before committing.
- `cargo clippy` warnings MUST be resolved or explicitly suppressed
with a justification comment.
- `cargo test` MUST pass with all tests green before merging to
master.
- Database schema changes MUST use Diesel migrations
(`diesel migration generate`), with hand-written SQL in `up.sql`
and `down.sql`, followed by `diesel print-schema` to regenerate
`schema.rs`.
- Features MUST be developed on named branches
(`###-feature-name`) and merged to master via pull request.
- File uploads MUST preserve existing files (append timestamp on
conflict, never overwrite).
## Governance
This constitution defines the non-negotiable architectural and
development standards for the ImageApi project. All code changes
MUST comply with these principles.
- **Amendments**: Any change to this constitution MUST be documented
with a version bump, rationale, and updated Sync Impact Report.
- **Versioning**: MAJOR for principle removals/redefinitions, MINOR
for new principles or material expansions, PATCH for wording
clarifications.
- **Compliance**: Pull request reviews SHOULD verify adherence to
these principles. The CLAUDE.md file provides runtime development
guidance and MUST remain consistent with this constitution.
**Version**: 1.0.0 | **Ratified**: 2026-02-26 | **Last Amended**: 2026-02-26

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@@ -0,0 +1,148 @@
#!/usr/bin/env pwsh
# Consolidated prerequisite checking script (PowerShell)
#
# This script provides unified prerequisite checking for Spec-Driven Development workflow.
# It replaces the functionality previously spread across multiple scripts.
#
# Usage: ./check-prerequisites.ps1 [OPTIONS]
#
# OPTIONS:
# -Json Output in JSON format
# -RequireTasks Require tasks.md to exist (for implementation phase)
# -IncludeTasks Include tasks.md in AVAILABLE_DOCS list
# -PathsOnly Only output path variables (no validation)
# -Help, -h Show help message
[CmdletBinding()]
param(
[switch]$Json,
[switch]$RequireTasks,
[switch]$IncludeTasks,
[switch]$PathsOnly,
[switch]$Help
)
$ErrorActionPreference = 'Stop'
# Show help if requested
if ($Help) {
Write-Output @"
Usage: check-prerequisites.ps1 [OPTIONS]
Consolidated prerequisite checking for Spec-Driven Development workflow.
OPTIONS:
-Json Output in JSON format
-RequireTasks Require tasks.md to exist (for implementation phase)
-IncludeTasks Include tasks.md in AVAILABLE_DOCS list
-PathsOnly Only output path variables (no prerequisite validation)
-Help, -h Show this help message
EXAMPLES:
# Check task prerequisites (plan.md required)
.\check-prerequisites.ps1 -Json
# Check implementation prerequisites (plan.md + tasks.md required)
.\check-prerequisites.ps1 -Json -RequireTasks -IncludeTasks
# Get feature paths only (no validation)
.\check-prerequisites.ps1 -PathsOnly
"@
exit 0
}
# Source common functions
. "$PSScriptRoot/common.ps1"
# Get feature paths and validate branch
$paths = Get-FeaturePathsEnv
if (-not (Test-FeatureBranch -Branch $paths.CURRENT_BRANCH -HasGit:$paths.HAS_GIT)) {
exit 1
}
# If paths-only mode, output paths and exit (support combined -Json -PathsOnly)
if ($PathsOnly) {
if ($Json) {
[PSCustomObject]@{
REPO_ROOT = $paths.REPO_ROOT
BRANCH = $paths.CURRENT_BRANCH
FEATURE_DIR = $paths.FEATURE_DIR
FEATURE_SPEC = $paths.FEATURE_SPEC
IMPL_PLAN = $paths.IMPL_PLAN
TASKS = $paths.TASKS
} | ConvertTo-Json -Compress
} else {
Write-Output "REPO_ROOT: $($paths.REPO_ROOT)"
Write-Output "BRANCH: $($paths.CURRENT_BRANCH)"
Write-Output "FEATURE_DIR: $($paths.FEATURE_DIR)"
Write-Output "FEATURE_SPEC: $($paths.FEATURE_SPEC)"
Write-Output "IMPL_PLAN: $($paths.IMPL_PLAN)"
Write-Output "TASKS: $($paths.TASKS)"
}
exit 0
}
# Validate required directories and files
if (-not (Test-Path $paths.FEATURE_DIR -PathType Container)) {
Write-Output "ERROR: Feature directory not found: $($paths.FEATURE_DIR)"
Write-Output "Run /speckit.specify first to create the feature structure."
exit 1
}
if (-not (Test-Path $paths.IMPL_PLAN -PathType Leaf)) {
Write-Output "ERROR: plan.md not found in $($paths.FEATURE_DIR)"
Write-Output "Run /speckit.plan first to create the implementation plan."
exit 1
}
# Check for tasks.md if required
if ($RequireTasks -and -not (Test-Path $paths.TASKS -PathType Leaf)) {
Write-Output "ERROR: tasks.md not found in $($paths.FEATURE_DIR)"
Write-Output "Run /speckit.tasks first to create the task list."
exit 1
}
# Build list of available documents
$docs = @()
# Always check these optional docs
if (Test-Path $paths.RESEARCH) { $docs += 'research.md' }
if (Test-Path $paths.DATA_MODEL) { $docs += 'data-model.md' }
# Check contracts directory (only if it exists and has files)
if ((Test-Path $paths.CONTRACTS_DIR) -and (Get-ChildItem -Path $paths.CONTRACTS_DIR -ErrorAction SilentlyContinue | Select-Object -First 1)) {
$docs += 'contracts/'
}
if (Test-Path $paths.QUICKSTART) { $docs += 'quickstart.md' }
# Include tasks.md if requested and it exists
if ($IncludeTasks -and (Test-Path $paths.TASKS)) {
$docs += 'tasks.md'
}
# Output results
if ($Json) {
# JSON output
[PSCustomObject]@{
FEATURE_DIR = $paths.FEATURE_DIR
AVAILABLE_DOCS = $docs
} | ConvertTo-Json -Compress
} else {
# Text output
Write-Output "FEATURE_DIR:$($paths.FEATURE_DIR)"
Write-Output "AVAILABLE_DOCS:"
# Show status of each potential document
Test-FileExists -Path $paths.RESEARCH -Description 'research.md' | Out-Null
Test-FileExists -Path $paths.DATA_MODEL -Description 'data-model.md' | Out-Null
Test-DirHasFiles -Path $paths.CONTRACTS_DIR -Description 'contracts/' | Out-Null
Test-FileExists -Path $paths.QUICKSTART -Description 'quickstart.md' | Out-Null
if ($IncludeTasks) {
Test-FileExists -Path $paths.TASKS -Description 'tasks.md' | Out-Null
}
}

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#!/usr/bin/env pwsh
# Common PowerShell functions analogous to common.sh
function Get-RepoRoot {
try {
$result = git rev-parse --show-toplevel 2>$null
if ($LASTEXITCODE -eq 0) {
return $result
}
} catch {
# Git command failed
}
# Fall back to script location for non-git repos
return (Resolve-Path (Join-Path $PSScriptRoot "../../..")).Path
}
function Get-CurrentBranch {
# First check if SPECIFY_FEATURE environment variable is set
if ($env:SPECIFY_FEATURE) {
return $env:SPECIFY_FEATURE
}
# Then check git if available
try {
$result = git rev-parse --abbrev-ref HEAD 2>$null
if ($LASTEXITCODE -eq 0) {
return $result
}
} catch {
# Git command failed
}
# For non-git repos, try to find the latest feature directory
$repoRoot = Get-RepoRoot
$specsDir = Join-Path $repoRoot "specs"
if (Test-Path $specsDir) {
$latestFeature = ""
$highest = 0
Get-ChildItem -Path $specsDir -Directory | ForEach-Object {
if ($_.Name -match '^(\d{3})-') {
$num = [int]$matches[1]
if ($num -gt $highest) {
$highest = $num
$latestFeature = $_.Name
}
}
}
if ($latestFeature) {
return $latestFeature
}
}
# Final fallback
return "main"
}
function Test-HasGit {
try {
git rev-parse --show-toplevel 2>$null | Out-Null
return ($LASTEXITCODE -eq 0)
} catch {
return $false
}
}
function Test-FeatureBranch {
param(
[string]$Branch,
[bool]$HasGit = $true
)
# For non-git repos, we can't enforce branch naming but still provide output
if (-not $HasGit) {
Write-Warning "[specify] Warning: Git repository not detected; skipped branch validation"
return $true
}
if ($Branch -notmatch '^[0-9]{3}-') {
Write-Output "ERROR: Not on a feature branch. Current branch: $Branch"
Write-Output "Feature branches should be named like: 001-feature-name"
return $false
}
return $true
}
function Get-FeatureDir {
param([string]$RepoRoot, [string]$Branch)
Join-Path $RepoRoot "specs/$Branch"
}
function Get-FeaturePathsEnv {
$repoRoot = Get-RepoRoot
$currentBranch = Get-CurrentBranch
$hasGit = Test-HasGit
$featureDir = Get-FeatureDir -RepoRoot $repoRoot -Branch $currentBranch
[PSCustomObject]@{
REPO_ROOT = $repoRoot
CURRENT_BRANCH = $currentBranch
HAS_GIT = $hasGit
FEATURE_DIR = $featureDir
FEATURE_SPEC = Join-Path $featureDir 'spec.md'
IMPL_PLAN = Join-Path $featureDir 'plan.md'
TASKS = Join-Path $featureDir 'tasks.md'
RESEARCH = Join-Path $featureDir 'research.md'
DATA_MODEL = Join-Path $featureDir 'data-model.md'
QUICKSTART = Join-Path $featureDir 'quickstart.md'
CONTRACTS_DIR = Join-Path $featureDir 'contracts'
}
}
function Test-FileExists {
param([string]$Path, [string]$Description)
if (Test-Path -Path $Path -PathType Leaf) {
Write-Output "$Description"
return $true
} else {
Write-Output "$Description"
return $false
}
}
function Test-DirHasFiles {
param([string]$Path, [string]$Description)
if ((Test-Path -Path $Path -PathType Container) -and (Get-ChildItem -Path $Path -ErrorAction SilentlyContinue | Where-Object { -not $_.PSIsContainer } | Select-Object -First 1)) {
Write-Output "$Description"
return $true
} else {
Write-Output "$Description"
return $false
}
}

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#!/usr/bin/env pwsh
# Create a new feature
[CmdletBinding()]
param(
[switch]$Json,
[string]$ShortName,
[int]$Number = 0,
[switch]$Help,
[Parameter(ValueFromRemainingArguments = $true)]
[string[]]$FeatureDescription
)
$ErrorActionPreference = 'Stop'
# Show help if requested
if ($Help) {
Write-Host "Usage: ./create-new-feature.ps1 [-Json] [-ShortName <name>] [-Number N] <feature description>"
Write-Host ""
Write-Host "Options:"
Write-Host " -Json Output in JSON format"
Write-Host " -ShortName <name> Provide a custom short name (2-4 words) for the branch"
Write-Host " -Number N Specify branch number manually (overrides auto-detection)"
Write-Host " -Help Show this help message"
Write-Host ""
Write-Host "Examples:"
Write-Host " ./create-new-feature.ps1 'Add user authentication system' -ShortName 'user-auth'"
Write-Host " ./create-new-feature.ps1 'Implement OAuth2 integration for API'"
exit 0
}
# Check if feature description provided
if (-not $FeatureDescription -or $FeatureDescription.Count -eq 0) {
Write-Error "Usage: ./create-new-feature.ps1 [-Json] [-ShortName <name>] <feature description>"
exit 1
}
$featureDesc = ($FeatureDescription -join ' ').Trim()
# Resolve repository root. Prefer git information when available, but fall back
# to searching for repository markers so the workflow still functions in repositories that
# were initialized with --no-git.
function Find-RepositoryRoot {
param(
[string]$StartDir,
[string[]]$Markers = @('.git', '.specify')
)
$current = Resolve-Path $StartDir
while ($true) {
foreach ($marker in $Markers) {
if (Test-Path (Join-Path $current $marker)) {
return $current
}
}
$parent = Split-Path $current -Parent
if ($parent -eq $current) {
# Reached filesystem root without finding markers
return $null
}
$current = $parent
}
}
function Get-HighestNumberFromSpecs {
param([string]$SpecsDir)
$highest = 0
if (Test-Path $SpecsDir) {
Get-ChildItem -Path $SpecsDir -Directory | ForEach-Object {
if ($_.Name -match '^(\d+)') {
$num = [int]$matches[1]
if ($num -gt $highest) { $highest = $num }
}
}
}
return $highest
}
function Get-HighestNumberFromBranches {
param()
$highest = 0
try {
$branches = git branch -a 2>$null
if ($LASTEXITCODE -eq 0) {
foreach ($branch in $branches) {
# Clean branch name: remove leading markers and remote prefixes
$cleanBranch = $branch.Trim() -replace '^\*?\s+', '' -replace '^remotes/[^/]+/', ''
# Extract feature number if branch matches pattern ###-*
if ($cleanBranch -match '^(\d+)-') {
$num = [int]$matches[1]
if ($num -gt $highest) { $highest = $num }
}
}
}
} catch {
# If git command fails, return 0
Write-Verbose "Could not check Git branches: $_"
}
return $highest
}
function Get-NextBranchNumber {
param(
[string]$SpecsDir
)
# Fetch all remotes to get latest branch info (suppress errors if no remotes)
try {
git fetch --all --prune 2>$null | Out-Null
} catch {
# Ignore fetch errors
}
# Get highest number from ALL branches (not just matching short name)
$highestBranch = Get-HighestNumberFromBranches
# Get highest number from ALL specs (not just matching short name)
$highestSpec = Get-HighestNumberFromSpecs -SpecsDir $SpecsDir
# Take the maximum of both
$maxNum = [Math]::Max($highestBranch, $highestSpec)
# Return next number
return $maxNum + 1
}
function ConvertTo-CleanBranchName {
param([string]$Name)
return $Name.ToLower() -replace '[^a-z0-9]', '-' -replace '-{2,}', '-' -replace '^-', '' -replace '-$', ''
}
$fallbackRoot = (Find-RepositoryRoot -StartDir $PSScriptRoot)
if (-not $fallbackRoot) {
Write-Error "Error: Could not determine repository root. Please run this script from within the repository."
exit 1
}
try {
$repoRoot = git rev-parse --show-toplevel 2>$null
if ($LASTEXITCODE -eq 0) {
$hasGit = $true
} else {
throw "Git not available"
}
} catch {
$repoRoot = $fallbackRoot
$hasGit = $false
}
Set-Location $repoRoot
$specsDir = Join-Path $repoRoot 'specs'
New-Item -ItemType Directory -Path $specsDir -Force | Out-Null
# Function to generate branch name with stop word filtering and length filtering
function Get-BranchName {
param([string]$Description)
# Common stop words to filter out
$stopWords = @(
'i', 'a', 'an', 'the', 'to', 'for', 'of', 'in', 'on', 'at', 'by', 'with', 'from',
'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had',
'do', 'does', 'did', 'will', 'would', 'should', 'could', 'can', 'may', 'might', 'must', 'shall',
'this', 'that', 'these', 'those', 'my', 'your', 'our', 'their',
'want', 'need', 'add', 'get', 'set'
)
# Convert to lowercase and extract words (alphanumeric only)
$cleanName = $Description.ToLower() -replace '[^a-z0-9\s]', ' '
$words = $cleanName -split '\s+' | Where-Object { $_ }
# Filter words: remove stop words and words shorter than 3 chars (unless they're uppercase acronyms in original)
$meaningfulWords = @()
foreach ($word in $words) {
# Skip stop words
if ($stopWords -contains $word) { continue }
# Keep words that are length >= 3 OR appear as uppercase in original (likely acronyms)
if ($word.Length -ge 3) {
$meaningfulWords += $word
} elseif ($Description -match "\b$($word.ToUpper())\b") {
# Keep short words if they appear as uppercase in original (likely acronyms)
$meaningfulWords += $word
}
}
# If we have meaningful words, use first 3-4 of them
if ($meaningfulWords.Count -gt 0) {
$maxWords = if ($meaningfulWords.Count -eq 4) { 4 } else { 3 }
$result = ($meaningfulWords | Select-Object -First $maxWords) -join '-'
return $result
} else {
# Fallback to original logic if no meaningful words found
$result = ConvertTo-CleanBranchName -Name $Description
$fallbackWords = ($result -split '-') | Where-Object { $_ } | Select-Object -First 3
return [string]::Join('-', $fallbackWords)
}
}
# Generate branch name
if ($ShortName) {
# Use provided short name, just clean it up
$branchSuffix = ConvertTo-CleanBranchName -Name $ShortName
} else {
# Generate from description with smart filtering
$branchSuffix = Get-BranchName -Description $featureDesc
}
# Determine branch number
if ($Number -eq 0) {
if ($hasGit) {
# Check existing branches on remotes
$Number = Get-NextBranchNumber -SpecsDir $specsDir
} else {
# Fall back to local directory check
$Number = (Get-HighestNumberFromSpecs -SpecsDir $specsDir) + 1
}
}
$featureNum = ('{0:000}' -f $Number)
$branchName = "$featureNum-$branchSuffix"
# GitHub enforces a 244-byte limit on branch names
# Validate and truncate if necessary
$maxBranchLength = 244
if ($branchName.Length -gt $maxBranchLength) {
# Calculate how much we need to trim from suffix
# Account for: feature number (3) + hyphen (1) = 4 chars
$maxSuffixLength = $maxBranchLength - 4
# Truncate suffix
$truncatedSuffix = $branchSuffix.Substring(0, [Math]::Min($branchSuffix.Length, $maxSuffixLength))
# Remove trailing hyphen if truncation created one
$truncatedSuffix = $truncatedSuffix -replace '-$', ''
$originalBranchName = $branchName
$branchName = "$featureNum-$truncatedSuffix"
Write-Warning "[specify] Branch name exceeded GitHub's 244-byte limit"
Write-Warning "[specify] Original: $originalBranchName ($($originalBranchName.Length) bytes)"
Write-Warning "[specify] Truncated to: $branchName ($($branchName.Length) bytes)"
}
if ($hasGit) {
try {
git checkout -b $branchName | Out-Null
} catch {
Write-Warning "Failed to create git branch: $branchName"
}
} else {
Write-Warning "[specify] Warning: Git repository not detected; skipped branch creation for $branchName"
}
$featureDir = Join-Path $specsDir $branchName
New-Item -ItemType Directory -Path $featureDir -Force | Out-Null
$template = Join-Path $repoRoot '.specify/templates/spec-template.md'
$specFile = Join-Path $featureDir 'spec.md'
if (Test-Path $template) {
Copy-Item $template $specFile -Force
} else {
New-Item -ItemType File -Path $specFile | Out-Null
}
# Set the SPECIFY_FEATURE environment variable for the current session
$env:SPECIFY_FEATURE = $branchName
if ($Json) {
$obj = [PSCustomObject]@{
BRANCH_NAME = $branchName
SPEC_FILE = $specFile
FEATURE_NUM = $featureNum
HAS_GIT = $hasGit
}
$obj | ConvertTo-Json -Compress
} else {
Write-Output "BRANCH_NAME: $branchName"
Write-Output "SPEC_FILE: $specFile"
Write-Output "FEATURE_NUM: $featureNum"
Write-Output "HAS_GIT: $hasGit"
Write-Output "SPECIFY_FEATURE environment variable set to: $branchName"
}

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#!/usr/bin/env pwsh
# Setup implementation plan for a feature
[CmdletBinding()]
param(
[switch]$Json,
[switch]$Help
)
$ErrorActionPreference = 'Stop'
# Show help if requested
if ($Help) {
Write-Output "Usage: ./setup-plan.ps1 [-Json] [-Help]"
Write-Output " -Json Output results in JSON format"
Write-Output " -Help Show this help message"
exit 0
}
# Load common functions
. "$PSScriptRoot/common.ps1"
# Get all paths and variables from common functions
$paths = Get-FeaturePathsEnv
# Check if we're on a proper feature branch (only for git repos)
if (-not (Test-FeatureBranch -Branch $paths.CURRENT_BRANCH -HasGit $paths.HAS_GIT)) {
exit 1
}
# Ensure the feature directory exists
New-Item -ItemType Directory -Path $paths.FEATURE_DIR -Force | Out-Null
# Copy plan template if it exists, otherwise note it or create empty file
$template = Join-Path $paths.REPO_ROOT '.specify/templates/plan-template.md'
if (Test-Path $template) {
Copy-Item $template $paths.IMPL_PLAN -Force
Write-Output "Copied plan template to $($paths.IMPL_PLAN)"
} else {
Write-Warning "Plan template not found at $template"
# Create a basic plan file if template doesn't exist
New-Item -ItemType File -Path $paths.IMPL_PLAN -Force | Out-Null
}
# Output results
if ($Json) {
$result = [PSCustomObject]@{
FEATURE_SPEC = $paths.FEATURE_SPEC
IMPL_PLAN = $paths.IMPL_PLAN
SPECS_DIR = $paths.FEATURE_DIR
BRANCH = $paths.CURRENT_BRANCH
HAS_GIT = $paths.HAS_GIT
}
$result | ConvertTo-Json -Compress
} else {
Write-Output "FEATURE_SPEC: $($paths.FEATURE_SPEC)"
Write-Output "IMPL_PLAN: $($paths.IMPL_PLAN)"
Write-Output "SPECS_DIR: $($paths.FEATURE_DIR)"
Write-Output "BRANCH: $($paths.CURRENT_BRANCH)"
Write-Output "HAS_GIT: $($paths.HAS_GIT)"
}

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#!/usr/bin/env pwsh
<#!
.SYNOPSIS
Update agent context files with information from plan.md (PowerShell version)
.DESCRIPTION
Mirrors the behavior of scripts/bash/update-agent-context.sh:
1. Environment Validation
2. Plan Data Extraction
3. Agent File Management (create from template or update existing)
4. Content Generation (technology stack, recent changes, timestamp)
5. Multi-Agent Support (claude, gemini, copilot, cursor-agent, qwen, opencode, codex, windsurf, kilocode, auggie, roo, codebuddy, amp, shai, q, agy, bob, qodercli)
.PARAMETER AgentType
Optional agent key to update a single agent. If omitted, updates all existing agent files (creating a default Claude file if none exist).
.EXAMPLE
./update-agent-context.ps1 -AgentType claude
.EXAMPLE
./update-agent-context.ps1 # Updates all existing agent files
.NOTES
Relies on common helper functions in common.ps1
#>
param(
[Parameter(Position=0)]
[ValidateSet('claude','gemini','copilot','cursor-agent','qwen','opencode','codex','windsurf','kilocode','auggie','roo','codebuddy','amp','shai','q','agy','bob','qodercli','generic')]
[string]$AgentType
)
$ErrorActionPreference = 'Stop'
# Import common helpers
$ScriptDir = Split-Path -Parent $MyInvocation.MyCommand.Path
. (Join-Path $ScriptDir 'common.ps1')
# Acquire environment paths
$envData = Get-FeaturePathsEnv
$REPO_ROOT = $envData.REPO_ROOT
$CURRENT_BRANCH = $envData.CURRENT_BRANCH
$HAS_GIT = $envData.HAS_GIT
$IMPL_PLAN = $envData.IMPL_PLAN
$NEW_PLAN = $IMPL_PLAN
# Agent file paths
$CLAUDE_FILE = Join-Path $REPO_ROOT 'CLAUDE.md'
$GEMINI_FILE = Join-Path $REPO_ROOT 'GEMINI.md'
$COPILOT_FILE = Join-Path $REPO_ROOT '.github/agents/copilot-instructions.md'
$CURSOR_FILE = Join-Path $REPO_ROOT '.cursor/rules/specify-rules.mdc'
$QWEN_FILE = Join-Path $REPO_ROOT 'QWEN.md'
$AGENTS_FILE = Join-Path $REPO_ROOT 'AGENTS.md'
$WINDSURF_FILE = Join-Path $REPO_ROOT '.windsurf/rules/specify-rules.md'
$KILOCODE_FILE = Join-Path $REPO_ROOT '.kilocode/rules/specify-rules.md'
$AUGGIE_FILE = Join-Path $REPO_ROOT '.augment/rules/specify-rules.md'
$ROO_FILE = Join-Path $REPO_ROOT '.roo/rules/specify-rules.md'
$CODEBUDDY_FILE = Join-Path $REPO_ROOT 'CODEBUDDY.md'
$QODER_FILE = Join-Path $REPO_ROOT 'QODER.md'
$AMP_FILE = Join-Path $REPO_ROOT 'AGENTS.md'
$SHAI_FILE = Join-Path $REPO_ROOT 'SHAI.md'
$Q_FILE = Join-Path $REPO_ROOT 'AGENTS.md'
$AGY_FILE = Join-Path $REPO_ROOT '.agent/rules/specify-rules.md'
$BOB_FILE = Join-Path $REPO_ROOT 'AGENTS.md'
$TEMPLATE_FILE = Join-Path $REPO_ROOT '.specify/templates/agent-file-template.md'
# Parsed plan data placeholders
$script:NEW_LANG = ''
$script:NEW_FRAMEWORK = ''
$script:NEW_DB = ''
$script:NEW_PROJECT_TYPE = ''
function Write-Info {
param(
[Parameter(Mandatory=$true)]
[string]$Message
)
Write-Host "INFO: $Message"
}
function Write-Success {
param(
[Parameter(Mandatory=$true)]
[string]$Message
)
Write-Host "$([char]0x2713) $Message"
}
function Write-WarningMsg {
param(
[Parameter(Mandatory=$true)]
[string]$Message
)
Write-Warning $Message
}
function Write-Err {
param(
[Parameter(Mandatory=$true)]
[string]$Message
)
Write-Host "ERROR: $Message" -ForegroundColor Red
}
function Validate-Environment {
if (-not $CURRENT_BRANCH) {
Write-Err 'Unable to determine current feature'
if ($HAS_GIT) { Write-Info "Make sure you're on a feature branch" } else { Write-Info 'Set SPECIFY_FEATURE environment variable or create a feature first' }
exit 1
}
if (-not (Test-Path $NEW_PLAN)) {
Write-Err "No plan.md found at $NEW_PLAN"
Write-Info 'Ensure you are working on a feature with a corresponding spec directory'
if (-not $HAS_GIT) { Write-Info 'Use: $env:SPECIFY_FEATURE=your-feature-name or create a new feature first' }
exit 1
}
if (-not (Test-Path $TEMPLATE_FILE)) {
Write-Err "Template file not found at $TEMPLATE_FILE"
Write-Info 'Run specify init to scaffold .specify/templates, or add agent-file-template.md there.'
exit 1
}
}
function Extract-PlanField {
param(
[Parameter(Mandatory=$true)]
[string]$FieldPattern,
[Parameter(Mandatory=$true)]
[string]$PlanFile
)
if (-not (Test-Path $PlanFile)) { return '' }
# Lines like **Language/Version**: Python 3.12
$regex = "^\*\*$([Regex]::Escape($FieldPattern))\*\*: (.+)$"
Get-Content -LiteralPath $PlanFile -Encoding utf8 | ForEach-Object {
if ($_ -match $regex) {
$val = $Matches[1].Trim()
if ($val -notin @('NEEDS CLARIFICATION','N/A')) { return $val }
}
} | Select-Object -First 1
}
function Parse-PlanData {
param(
[Parameter(Mandatory=$true)]
[string]$PlanFile
)
if (-not (Test-Path $PlanFile)) { Write-Err "Plan file not found: $PlanFile"; return $false }
Write-Info "Parsing plan data from $PlanFile"
$script:NEW_LANG = Extract-PlanField -FieldPattern 'Language/Version' -PlanFile $PlanFile
$script:NEW_FRAMEWORK = Extract-PlanField -FieldPattern 'Primary Dependencies' -PlanFile $PlanFile
$script:NEW_DB = Extract-PlanField -FieldPattern 'Storage' -PlanFile $PlanFile
$script:NEW_PROJECT_TYPE = Extract-PlanField -FieldPattern 'Project Type' -PlanFile $PlanFile
if ($NEW_LANG) { Write-Info "Found language: $NEW_LANG" } else { Write-WarningMsg 'No language information found in plan' }
if ($NEW_FRAMEWORK) { Write-Info "Found framework: $NEW_FRAMEWORK" }
if ($NEW_DB -and $NEW_DB -ne 'N/A') { Write-Info "Found database: $NEW_DB" }
if ($NEW_PROJECT_TYPE) { Write-Info "Found project type: $NEW_PROJECT_TYPE" }
return $true
}
function Format-TechnologyStack {
param(
[Parameter(Mandatory=$false)]
[string]$Lang,
[Parameter(Mandatory=$false)]
[string]$Framework
)
$parts = @()
if ($Lang -and $Lang -ne 'NEEDS CLARIFICATION') { $parts += $Lang }
if ($Framework -and $Framework -notin @('NEEDS CLARIFICATION','N/A')) { $parts += $Framework }
if (-not $parts) { return '' }
return ($parts -join ' + ')
}
function Get-ProjectStructure {
param(
[Parameter(Mandatory=$false)]
[string]$ProjectType
)
if ($ProjectType -match 'web') { return "backend/`nfrontend/`ntests/" } else { return "src/`ntests/" }
}
function Get-CommandsForLanguage {
param(
[Parameter(Mandatory=$false)]
[string]$Lang
)
switch -Regex ($Lang) {
'Python' { return "cd src; pytest; ruff check ." }
'Rust' { return "cargo test; cargo clippy" }
'JavaScript|TypeScript' { return "npm test; npm run lint" }
default { return "# Add commands for $Lang" }
}
}
function Get-LanguageConventions {
param(
[Parameter(Mandatory=$false)]
[string]$Lang
)
if ($Lang) { "${Lang}: Follow standard conventions" } else { 'General: Follow standard conventions' }
}
function New-AgentFile {
param(
[Parameter(Mandatory=$true)]
[string]$TargetFile,
[Parameter(Mandatory=$true)]
[string]$ProjectName,
[Parameter(Mandatory=$true)]
[datetime]$Date
)
if (-not (Test-Path $TEMPLATE_FILE)) { Write-Err "Template not found at $TEMPLATE_FILE"; return $false }
$temp = New-TemporaryFile
Copy-Item -LiteralPath $TEMPLATE_FILE -Destination $temp -Force
$projectStructure = Get-ProjectStructure -ProjectType $NEW_PROJECT_TYPE
$commands = Get-CommandsForLanguage -Lang $NEW_LANG
$languageConventions = Get-LanguageConventions -Lang $NEW_LANG
$escaped_lang = $NEW_LANG
$escaped_framework = $NEW_FRAMEWORK
$escaped_branch = $CURRENT_BRANCH
$content = Get-Content -LiteralPath $temp -Raw -Encoding utf8
$content = $content -replace '\[PROJECT NAME\]',$ProjectName
$content = $content -replace '\[DATE\]',$Date.ToString('yyyy-MM-dd')
# Build the technology stack string safely
$techStackForTemplate = ""
if ($escaped_lang -and $escaped_framework) {
$techStackForTemplate = "- $escaped_lang + $escaped_framework ($escaped_branch)"
} elseif ($escaped_lang) {
$techStackForTemplate = "- $escaped_lang ($escaped_branch)"
} elseif ($escaped_framework) {
$techStackForTemplate = "- $escaped_framework ($escaped_branch)"
}
$content = $content -replace '\[EXTRACTED FROM ALL PLAN.MD FILES\]',$techStackForTemplate
# For project structure we manually embed (keep newlines)
$escapedStructure = [Regex]::Escape($projectStructure)
$content = $content -replace '\[ACTUAL STRUCTURE FROM PLANS\]',$escapedStructure
# Replace escaped newlines placeholder after all replacements
$content = $content -replace '\[ONLY COMMANDS FOR ACTIVE TECHNOLOGIES\]',$commands
$content = $content -replace '\[LANGUAGE-SPECIFIC, ONLY FOR LANGUAGES IN USE\]',$languageConventions
# Build the recent changes string safely
$recentChangesForTemplate = ""
if ($escaped_lang -and $escaped_framework) {
$recentChangesForTemplate = "- ${escaped_branch}: Added ${escaped_lang} + ${escaped_framework}"
} elseif ($escaped_lang) {
$recentChangesForTemplate = "- ${escaped_branch}: Added ${escaped_lang}"
} elseif ($escaped_framework) {
$recentChangesForTemplate = "- ${escaped_branch}: Added ${escaped_framework}"
}
$content = $content -replace '\[LAST 3 FEATURES AND WHAT THEY ADDED\]',$recentChangesForTemplate
# Convert literal \n sequences introduced by Escape to real newlines
$content = $content -replace '\\n',[Environment]::NewLine
$parent = Split-Path -Parent $TargetFile
if (-not (Test-Path $parent)) { New-Item -ItemType Directory -Path $parent | Out-Null }
Set-Content -LiteralPath $TargetFile -Value $content -NoNewline -Encoding utf8
Remove-Item $temp -Force
return $true
}
function Update-ExistingAgentFile {
param(
[Parameter(Mandatory=$true)]
[string]$TargetFile,
[Parameter(Mandatory=$true)]
[datetime]$Date
)
if (-not (Test-Path $TargetFile)) { return (New-AgentFile -TargetFile $TargetFile -ProjectName (Split-Path $REPO_ROOT -Leaf) -Date $Date) }
$techStack = Format-TechnologyStack -Lang $NEW_LANG -Framework $NEW_FRAMEWORK
$newTechEntries = @()
if ($techStack) {
$escapedTechStack = [Regex]::Escape($techStack)
if (-not (Select-String -Pattern $escapedTechStack -Path $TargetFile -Quiet)) {
$newTechEntries += "- $techStack ($CURRENT_BRANCH)"
}
}
if ($NEW_DB -and $NEW_DB -notin @('N/A','NEEDS CLARIFICATION')) {
$escapedDB = [Regex]::Escape($NEW_DB)
if (-not (Select-String -Pattern $escapedDB -Path $TargetFile -Quiet)) {
$newTechEntries += "- $NEW_DB ($CURRENT_BRANCH)"
}
}
$newChangeEntry = ''
if ($techStack) { $newChangeEntry = "- ${CURRENT_BRANCH}: Added ${techStack}" }
elseif ($NEW_DB -and $NEW_DB -notin @('N/A','NEEDS CLARIFICATION')) { $newChangeEntry = "- ${CURRENT_BRANCH}: Added ${NEW_DB}" }
$lines = Get-Content -LiteralPath $TargetFile -Encoding utf8
$output = New-Object System.Collections.Generic.List[string]
$inTech = $false; $inChanges = $false; $techAdded = $false; $changeAdded = $false; $existingChanges = 0
for ($i=0; $i -lt $lines.Count; $i++) {
$line = $lines[$i]
if ($line -eq '## Active Technologies') {
$output.Add($line)
$inTech = $true
continue
}
if ($inTech -and $line -match '^##\s') {
if (-not $techAdded -and $newTechEntries.Count -gt 0) { $newTechEntries | ForEach-Object { $output.Add($_) }; $techAdded = $true }
$output.Add($line); $inTech = $false; continue
}
if ($inTech -and [string]::IsNullOrWhiteSpace($line)) {
if (-not $techAdded -and $newTechEntries.Count -gt 0) { $newTechEntries | ForEach-Object { $output.Add($_) }; $techAdded = $true }
$output.Add($line); continue
}
if ($line -eq '## Recent Changes') {
$output.Add($line)
if ($newChangeEntry) { $output.Add($newChangeEntry); $changeAdded = $true }
$inChanges = $true
continue
}
if ($inChanges -and $line -match '^##\s') { $output.Add($line); $inChanges = $false; continue }
if ($inChanges -and $line -match '^- ') {
if ($existingChanges -lt 2) { $output.Add($line); $existingChanges++ }
continue
}
if ($line -match '\*\*Last updated\*\*: .*\d{4}-\d{2}-\d{2}') {
$output.Add(($line -replace '\d{4}-\d{2}-\d{2}',$Date.ToString('yyyy-MM-dd')))
continue
}
$output.Add($line)
}
# Post-loop check: if we're still in the Active Technologies section and haven't added new entries
if ($inTech -and -not $techAdded -and $newTechEntries.Count -gt 0) {
$newTechEntries | ForEach-Object { $output.Add($_) }
}
Set-Content -LiteralPath $TargetFile -Value ($output -join [Environment]::NewLine) -Encoding utf8
return $true
}
function Update-AgentFile {
param(
[Parameter(Mandatory=$true)]
[string]$TargetFile,
[Parameter(Mandatory=$true)]
[string]$AgentName
)
if (-not $TargetFile -or -not $AgentName) { Write-Err 'Update-AgentFile requires TargetFile and AgentName'; return $false }
Write-Info "Updating $AgentName context file: $TargetFile"
$projectName = Split-Path $REPO_ROOT -Leaf
$date = Get-Date
$dir = Split-Path -Parent $TargetFile
if (-not (Test-Path $dir)) { New-Item -ItemType Directory -Path $dir | Out-Null }
if (-not (Test-Path $TargetFile)) {
if (New-AgentFile -TargetFile $TargetFile -ProjectName $projectName -Date $date) { Write-Success "Created new $AgentName context file" } else { Write-Err 'Failed to create new agent file'; return $false }
} else {
try {
if (Update-ExistingAgentFile -TargetFile $TargetFile -Date $date) { Write-Success "Updated existing $AgentName context file" } else { Write-Err 'Failed to update agent file'; return $false }
} catch {
Write-Err "Cannot access or update existing file: $TargetFile. $_"
return $false
}
}
return $true
}
function Update-SpecificAgent {
param(
[Parameter(Mandatory=$true)]
[string]$Type
)
switch ($Type) {
'claude' { Update-AgentFile -TargetFile $CLAUDE_FILE -AgentName 'Claude Code' }
'gemini' { Update-AgentFile -TargetFile $GEMINI_FILE -AgentName 'Gemini CLI' }
'copilot' { Update-AgentFile -TargetFile $COPILOT_FILE -AgentName 'GitHub Copilot' }
'cursor-agent' { Update-AgentFile -TargetFile $CURSOR_FILE -AgentName 'Cursor IDE' }
'qwen' { Update-AgentFile -TargetFile $QWEN_FILE -AgentName 'Qwen Code' }
'opencode' { Update-AgentFile -TargetFile $AGENTS_FILE -AgentName 'opencode' }
'codex' { Update-AgentFile -TargetFile $AGENTS_FILE -AgentName 'Codex CLI' }
'windsurf' { Update-AgentFile -TargetFile $WINDSURF_FILE -AgentName 'Windsurf' }
'kilocode' { Update-AgentFile -TargetFile $KILOCODE_FILE -AgentName 'Kilo Code' }
'auggie' { Update-AgentFile -TargetFile $AUGGIE_FILE -AgentName 'Auggie CLI' }
'roo' { Update-AgentFile -TargetFile $ROO_FILE -AgentName 'Roo Code' }
'codebuddy' { Update-AgentFile -TargetFile $CODEBUDDY_FILE -AgentName 'CodeBuddy CLI' }
'qodercli' { Update-AgentFile -TargetFile $QODER_FILE -AgentName 'Qoder CLI' }
'amp' { Update-AgentFile -TargetFile $AMP_FILE -AgentName 'Amp' }
'shai' { Update-AgentFile -TargetFile $SHAI_FILE -AgentName 'SHAI' }
'q' { Update-AgentFile -TargetFile $Q_FILE -AgentName 'Amazon Q Developer CLI' }
'agy' { Update-AgentFile -TargetFile $AGY_FILE -AgentName 'Antigravity' }
'bob' { Update-AgentFile -TargetFile $BOB_FILE -AgentName 'IBM Bob' }
'generic' { Write-Info 'Generic agent: no predefined context file. Use the agent-specific update script for your agent.' }
default { Write-Err "Unknown agent type '$Type'"; Write-Err 'Expected: claude|gemini|copilot|cursor-agent|qwen|opencode|codex|windsurf|kilocode|auggie|roo|codebuddy|amp|shai|q|agy|bob|qodercli|generic'; return $false }
}
}
function Update-AllExistingAgents {
$found = $false
$ok = $true
if (Test-Path $CLAUDE_FILE) { if (-not (Update-AgentFile -TargetFile $CLAUDE_FILE -AgentName 'Claude Code')) { $ok = $false }; $found = $true }
if (Test-Path $GEMINI_FILE) { if (-not (Update-AgentFile -TargetFile $GEMINI_FILE -AgentName 'Gemini CLI')) { $ok = $false }; $found = $true }
if (Test-Path $COPILOT_FILE) { if (-not (Update-AgentFile -TargetFile $COPILOT_FILE -AgentName 'GitHub Copilot')) { $ok = $false }; $found = $true }
if (Test-Path $CURSOR_FILE) { if (-not (Update-AgentFile -TargetFile $CURSOR_FILE -AgentName 'Cursor IDE')) { $ok = $false }; $found = $true }
if (Test-Path $QWEN_FILE) { if (-not (Update-AgentFile -TargetFile $QWEN_FILE -AgentName 'Qwen Code')) { $ok = $false }; $found = $true }
if (Test-Path $AGENTS_FILE) { if (-not (Update-AgentFile -TargetFile $AGENTS_FILE -AgentName 'Codex/opencode')) { $ok = $false }; $found = $true }
if (Test-Path $WINDSURF_FILE) { if (-not (Update-AgentFile -TargetFile $WINDSURF_FILE -AgentName 'Windsurf')) { $ok = $false }; $found = $true }
if (Test-Path $KILOCODE_FILE) { if (-not (Update-AgentFile -TargetFile $KILOCODE_FILE -AgentName 'Kilo Code')) { $ok = $false }; $found = $true }
if (Test-Path $AUGGIE_FILE) { if (-not (Update-AgentFile -TargetFile $AUGGIE_FILE -AgentName 'Auggie CLI')) { $ok = $false }; $found = $true }
if (Test-Path $ROO_FILE) { if (-not (Update-AgentFile -TargetFile $ROO_FILE -AgentName 'Roo Code')) { $ok = $false }; $found = $true }
if (Test-Path $CODEBUDDY_FILE) { if (-not (Update-AgentFile -TargetFile $CODEBUDDY_FILE -AgentName 'CodeBuddy CLI')) { $ok = $false }; $found = $true }
if (Test-Path $QODER_FILE) { if (-not (Update-AgentFile -TargetFile $QODER_FILE -AgentName 'Qoder CLI')) { $ok = $false }; $found = $true }
if (Test-Path $SHAI_FILE) { if (-not (Update-AgentFile -TargetFile $SHAI_FILE -AgentName 'SHAI')) { $ok = $false }; $found = $true }
if (Test-Path $Q_FILE) { if (-not (Update-AgentFile -TargetFile $Q_FILE -AgentName 'Amazon Q Developer CLI')) { $ok = $false }; $found = $true }
if (Test-Path $AGY_FILE) { if (-not (Update-AgentFile -TargetFile $AGY_FILE -AgentName 'Antigravity')) { $ok = $false }; $found = $true }
if (Test-Path $BOB_FILE) { if (-not (Update-AgentFile -TargetFile $BOB_FILE -AgentName 'IBM Bob')) { $ok = $false }; $found = $true }
if (-not $found) {
Write-Info 'No existing agent files found, creating default Claude file...'
if (-not (Update-AgentFile -TargetFile $CLAUDE_FILE -AgentName 'Claude Code')) { $ok = $false }
}
return $ok
}
function Print-Summary {
Write-Host ''
Write-Info 'Summary of changes:'
if ($NEW_LANG) { Write-Host " - Added language: $NEW_LANG" }
if ($NEW_FRAMEWORK) { Write-Host " - Added framework: $NEW_FRAMEWORK" }
if ($NEW_DB -and $NEW_DB -ne 'N/A') { Write-Host " - Added database: $NEW_DB" }
Write-Host ''
Write-Info 'Usage: ./update-agent-context.ps1 [-AgentType claude|gemini|copilot|cursor-agent|qwen|opencode|codex|windsurf|kilocode|auggie|roo|codebuddy|amp|shai|q|agy|bob|qodercli|generic]'
}
function Main {
Validate-Environment
Write-Info "=== Updating agent context files for feature $CURRENT_BRANCH ==="
if (-not (Parse-PlanData -PlanFile $NEW_PLAN)) { Write-Err 'Failed to parse plan data'; exit 1 }
$success = $true
if ($AgentType) {
Write-Info "Updating specific agent: $AgentType"
if (-not (Update-SpecificAgent -Type $AgentType)) { $success = $false }
}
else {
Write-Info 'No agent specified, updating all existing agent files...'
if (-not (Update-AllExistingAgents)) { $success = $false }
}
Print-Summary
if ($success) { Write-Success 'Agent context update completed successfully'; exit 0 } else { Write-Err 'Agent context update completed with errors'; exit 1 }
}
Main

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# [PROJECT NAME] Development Guidelines
Auto-generated from all feature plans. Last updated: [DATE]
## Active Technologies
[EXTRACTED FROM ALL PLAN.MD FILES]
## Project Structure
```text
[ACTUAL STRUCTURE FROM PLANS]
```
## Commands
[ONLY COMMANDS FOR ACTIVE TECHNOLOGIES]
## Code Style
[LANGUAGE-SPECIFIC, ONLY FOR LANGUAGES IN USE]
## Recent Changes
[LAST 3 FEATURES AND WHAT THEY ADDED]
<!-- MANUAL ADDITIONS START -->
<!-- MANUAL ADDITIONS END -->

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# [CHECKLIST TYPE] Checklist: [FEATURE NAME]
**Purpose**: [Brief description of what this checklist covers]
**Created**: [DATE]
**Feature**: [Link to spec.md or relevant documentation]
**Note**: This checklist is generated by the `/speckit.checklist` command based on feature context and requirements.
<!--
============================================================================
IMPORTANT: The checklist items below are SAMPLE ITEMS for illustration only.
The /speckit.checklist command MUST replace these with actual items based on:
- User's specific checklist request
- Feature requirements from spec.md
- Technical context from plan.md
- Implementation details from tasks.md
DO NOT keep these sample items in the generated checklist file.
============================================================================
-->
## [Category 1]
- [ ] CHK001 First checklist item with clear action
- [ ] CHK002 Second checklist item
- [ ] CHK003 Third checklist item
## [Category 2]
- [ ] CHK004 Another category item
- [ ] CHK005 Item with specific criteria
- [ ] CHK006 Final item in this category
## Notes
- Check items off as completed: `[x]`
- Add comments or findings inline
- Link to relevant resources or documentation
- Items are numbered sequentially for easy reference

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# [PROJECT_NAME] Constitution
<!-- Example: Spec Constitution, TaskFlow Constitution, etc. -->
## Core Principles
### [PRINCIPLE_1_NAME]
<!-- Example: I. Library-First -->
[PRINCIPLE_1_DESCRIPTION]
<!-- Example: Every feature starts as a standalone library; Libraries must be self-contained, independently testable, documented; Clear purpose required - no organizational-only libraries -->
### [PRINCIPLE_2_NAME]
<!-- Example: II. CLI Interface -->
[PRINCIPLE_2_DESCRIPTION]
<!-- Example: Every library exposes functionality via CLI; Text in/out protocol: stdin/args → stdout, errors → stderr; Support JSON + human-readable formats -->
### [PRINCIPLE_3_NAME]
<!-- Example: III. Test-First (NON-NEGOTIABLE) -->
[PRINCIPLE_3_DESCRIPTION]
<!-- Example: TDD mandatory: Tests written → User approved → Tests fail → Then implement; Red-Green-Refactor cycle strictly enforced -->
### [PRINCIPLE_4_NAME]
<!-- Example: IV. Integration Testing -->
[PRINCIPLE_4_DESCRIPTION]
<!-- Example: Focus areas requiring integration tests: New library contract tests, Contract changes, Inter-service communication, Shared schemas -->
### [PRINCIPLE_5_NAME]
<!-- Example: V. Observability, VI. Versioning & Breaking Changes, VII. Simplicity -->
[PRINCIPLE_5_DESCRIPTION]
<!-- Example: Text I/O ensures debuggability; Structured logging required; Or: MAJOR.MINOR.BUILD format; Or: Start simple, YAGNI principles -->
## [SECTION_2_NAME]
<!-- Example: Additional Constraints, Security Requirements, Performance Standards, etc. -->
[SECTION_2_CONTENT]
<!-- Example: Technology stack requirements, compliance standards, deployment policies, etc. -->
## [SECTION_3_NAME]
<!-- Example: Development Workflow, Review Process, Quality Gates, etc. -->
[SECTION_3_CONTENT]
<!-- Example: Code review requirements, testing gates, deployment approval process, etc. -->
## Governance
<!-- Example: Constitution supersedes all other practices; Amendments require documentation, approval, migration plan -->
[GOVERNANCE_RULES]
<!-- Example: All PRs/reviews must verify compliance; Complexity must be justified; Use [GUIDANCE_FILE] for runtime development guidance -->
**Version**: [CONSTITUTION_VERSION] | **Ratified**: [RATIFICATION_DATE] | **Last Amended**: [LAST_AMENDED_DATE]
<!-- Example: Version: 2.1.1 | Ratified: 2025-06-13 | Last Amended: 2025-07-16 -->

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# Implementation Plan: [FEATURE]
**Branch**: `[###-feature-name]` | **Date**: [DATE] | **Spec**: [link]
**Input**: Feature specification from `/specs/[###-feature-name]/spec.md`
**Note**: This template is filled in by the `/speckit.plan` command. See `.specify/templates/plan-template.md` for the execution workflow.
## Summary
[Extract from feature spec: primary requirement + technical approach from research]
## Technical Context
<!--
ACTION REQUIRED: Replace the content in this section with the technical details
for the project. The structure here is presented in advisory capacity to guide
the iteration process.
-->
**Language/Version**: [e.g., Python 3.11, Swift 5.9, Rust 1.75 or NEEDS CLARIFICATION]
**Primary Dependencies**: [e.g., FastAPI, UIKit, LLVM or NEEDS CLARIFICATION]
**Storage**: [if applicable, e.g., PostgreSQL, CoreData, files or N/A]
**Testing**: [e.g., pytest, XCTest, cargo test or NEEDS CLARIFICATION]
**Target Platform**: [e.g., Linux server, iOS 15+, WASM or NEEDS CLARIFICATION]
**Project Type**: [e.g., library/cli/web-service/mobile-app/compiler/desktop-app or NEEDS CLARIFICATION]
**Performance Goals**: [domain-specific, e.g., 1000 req/s, 10k lines/sec, 60 fps or NEEDS CLARIFICATION]
**Constraints**: [domain-specific, e.g., <200ms p95, <100MB memory, offline-capable or NEEDS CLARIFICATION]
**Scale/Scope**: [domain-specific, e.g., 10k users, 1M LOC, 50 screens or NEEDS CLARIFICATION]
## Constitution Check
*GATE: Must pass before Phase 0 research. Re-check after Phase 1 design.*
[Gates determined based on constitution file]
## Project Structure
### Documentation (this feature)
```text
specs/[###-feature]/
├── plan.md # This file (/speckit.plan command output)
├── research.md # Phase 0 output (/speckit.plan command)
├── data-model.md # Phase 1 output (/speckit.plan command)
├── quickstart.md # Phase 1 output (/speckit.plan command)
├── contracts/ # Phase 1 output (/speckit.plan command)
└── tasks.md # Phase 2 output (/speckit.tasks command - NOT created by /speckit.plan)
```
### Source Code (repository root)
<!--
ACTION REQUIRED: Replace the placeholder tree below with the concrete layout
for this feature. Delete unused options and expand the chosen structure with
real paths (e.g., apps/admin, packages/something). The delivered plan must
not include Option labels.
-->
```text
# [REMOVE IF UNUSED] Option 1: Single project (DEFAULT)
src/
├── models/
├── services/
├── cli/
└── lib/
tests/
├── contract/
├── integration/
└── unit/
# [REMOVE IF UNUSED] Option 2: Web application (when "frontend" + "backend" detected)
backend/
├── src/
│ ├── models/
│ ├── services/
│ └── api/
└── tests/
frontend/
├── src/
│ ├── components/
│ ├── pages/
│ └── services/
└── tests/
# [REMOVE IF UNUSED] Option 3: Mobile + API (when "iOS/Android" detected)
api/
└── [same as backend above]
ios/ or android/
└── [platform-specific structure: feature modules, UI flows, platform tests]
```
**Structure Decision**: [Document the selected structure and reference the real
directories captured above]
## Complexity Tracking
> **Fill ONLY if Constitution Check has violations that must be justified**
| Violation | Why Needed | Simpler Alternative Rejected Because |
|-----------|------------|-------------------------------------|
| [e.g., 4th project] | [current need] | [why 3 projects insufficient] |
| [e.g., Repository pattern] | [specific problem] | [why direct DB access insufficient] |

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# Feature Specification: [FEATURE NAME]
**Feature Branch**: `[###-feature-name]`
**Created**: [DATE]
**Status**: Draft
**Input**: User description: "$ARGUMENTS"
## User Scenarios & Testing *(mandatory)*
<!--
IMPORTANT: User stories should be PRIORITIZED as user journeys ordered by importance.
Each user story/journey must be INDEPENDENTLY TESTABLE - meaning if you implement just ONE of them,
you should still have a viable MVP (Minimum Viable Product) that delivers value.
Assign priorities (P1, P2, P3, etc.) to each story, where P1 is the most critical.
Think of each story as a standalone slice of functionality that can be:
- Developed independently
- Tested independently
- Deployed independently
- Demonstrated to users independently
-->
### User Story 1 - [Brief Title] (Priority: P1)
[Describe this user journey in plain language]
**Why this priority**: [Explain the value and why it has this priority level]
**Independent Test**: [Describe how this can be tested independently - e.g., "Can be fully tested by [specific action] and delivers [specific value]"]
**Acceptance Scenarios**:
1. **Given** [initial state], **When** [action], **Then** [expected outcome]
2. **Given** [initial state], **When** [action], **Then** [expected outcome]
---
### User Story 2 - [Brief Title] (Priority: P2)
[Describe this user journey in plain language]
**Why this priority**: [Explain the value and why it has this priority level]
**Independent Test**: [Describe how this can be tested independently]
**Acceptance Scenarios**:
1. **Given** [initial state], **When** [action], **Then** [expected outcome]
---
### User Story 3 - [Brief Title] (Priority: P3)
[Describe this user journey in plain language]
**Why this priority**: [Explain the value and why it has this priority level]
**Independent Test**: [Describe how this can be tested independently]
**Acceptance Scenarios**:
1. **Given** [initial state], **When** [action], **Then** [expected outcome]
---
[Add more user stories as needed, each with an assigned priority]
### Edge Cases
<!--
ACTION REQUIRED: The content in this section represents placeholders.
Fill them out with the right edge cases.
-->
- What happens when [boundary condition]?
- How does system handle [error scenario]?
## Requirements *(mandatory)*
<!--
ACTION REQUIRED: The content in this section represents placeholders.
Fill them out with the right functional requirements.
-->
### Functional Requirements
- **FR-001**: System MUST [specific capability, e.g., "allow users to create accounts"]
- **FR-002**: System MUST [specific capability, e.g., "validate email addresses"]
- **FR-003**: Users MUST be able to [key interaction, e.g., "reset their password"]
- **FR-004**: System MUST [data requirement, e.g., "persist user preferences"]
- **FR-005**: System MUST [behavior, e.g., "log all security events"]
*Example of marking unclear requirements:*
- **FR-006**: System MUST authenticate users via [NEEDS CLARIFICATION: auth method not specified - email/password, SSO, OAuth?]
- **FR-007**: System MUST retain user data for [NEEDS CLARIFICATION: retention period not specified]
### Key Entities *(include if feature involves data)*
- **[Entity 1]**: [What it represents, key attributes without implementation]
- **[Entity 2]**: [What it represents, relationships to other entities]
## Success Criteria *(mandatory)*
<!--
ACTION REQUIRED: Define measurable success criteria.
These must be technology-agnostic and measurable.
-->
### Measurable Outcomes
- **SC-001**: [Measurable metric, e.g., "Users can complete account creation in under 2 minutes"]
- **SC-002**: [Measurable metric, e.g., "System handles 1000 concurrent users without degradation"]
- **SC-003**: [User satisfaction metric, e.g., "90% of users successfully complete primary task on first attempt"]
- **SC-004**: [Business metric, e.g., "Reduce support tickets related to [X] by 50%"]

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---
description: "Task list template for feature implementation"
---
# Tasks: [FEATURE NAME]
**Input**: Design documents from `/specs/[###-feature-name]/`
**Prerequisites**: plan.md (required), spec.md (required for user stories), research.md, data-model.md, contracts/
**Tests**: The examples below include test tasks. Tests are OPTIONAL - only include them if explicitly requested in the feature specification.
**Organization**: Tasks are grouped by user story to enable independent implementation and testing of each story.
## Format: `[ID] [P?] [Story] Description`
- **[P]**: Can run in parallel (different files, no dependencies)
- **[Story]**: Which user story this task belongs to (e.g., US1, US2, US3)
- Include exact file paths in descriptions
## Path Conventions
- **Single project**: `src/`, `tests/` at repository root
- **Web app**: `backend/src/`, `frontend/src/`
- **Mobile**: `api/src/`, `ios/src/` or `android/src/`
- Paths shown below assume single project - adjust based on plan.md structure
<!--
============================================================================
IMPORTANT: The tasks below are SAMPLE TASKS for illustration purposes only.
The /speckit.tasks command MUST replace these with actual tasks based on:
- User stories from spec.md (with their priorities P1, P2, P3...)
- Feature requirements from plan.md
- Entities from data-model.md
- Endpoints from contracts/
Tasks MUST be organized by user story so each story can be:
- Implemented independently
- Tested independently
- Delivered as an MVP increment
DO NOT keep these sample tasks in the generated tasks.md file.
============================================================================
-->
## Phase 1: Setup (Shared Infrastructure)
**Purpose**: Project initialization and basic structure
- [ ] T001 Create project structure per implementation plan
- [ ] T002 Initialize [language] project with [framework] dependencies
- [ ] T003 [P] Configure linting and formatting tools
---
## Phase 2: Foundational (Blocking Prerequisites)
**Purpose**: Core infrastructure that MUST be complete before ANY user story can be implemented
**⚠️ CRITICAL**: No user story work can begin until this phase is complete
Examples of foundational tasks (adjust based on your project):
- [ ] T004 Setup database schema and migrations framework
- [ ] T005 [P] Implement authentication/authorization framework
- [ ] T006 [P] Setup API routing and middleware structure
- [ ] T007 Create base models/entities that all stories depend on
- [ ] T008 Configure error handling and logging infrastructure
- [ ] T009 Setup environment configuration management
**Checkpoint**: Foundation ready - user story implementation can now begin in parallel
---
## Phase 3: User Story 1 - [Title] (Priority: P1) 🎯 MVP
**Goal**: [Brief description of what this story delivers]
**Independent Test**: [How to verify this story works on its own]
### Tests for User Story 1 (OPTIONAL - only if tests requested) ⚠️
> **NOTE: Write these tests FIRST, ensure they FAIL before implementation**
- [ ] T010 [P] [US1] Contract test for [endpoint] in tests/contract/test_[name].py
- [ ] T011 [P] [US1] Integration test for [user journey] in tests/integration/test_[name].py
### Implementation for User Story 1
- [ ] T012 [P] [US1] Create [Entity1] model in src/models/[entity1].py
- [ ] T013 [P] [US1] Create [Entity2] model in src/models/[entity2].py
- [ ] T014 [US1] Implement [Service] in src/services/[service].py (depends on T012, T013)
- [ ] T015 [US1] Implement [endpoint/feature] in src/[location]/[file].py
- [ ] T016 [US1] Add validation and error handling
- [ ] T017 [US1] Add logging for user story 1 operations
**Checkpoint**: At this point, User Story 1 should be fully functional and testable independently
---
## Phase 4: User Story 2 - [Title] (Priority: P2)
**Goal**: [Brief description of what this story delivers]
**Independent Test**: [How to verify this story works on its own]
### Tests for User Story 2 (OPTIONAL - only if tests requested) ⚠️
- [ ] T018 [P] [US2] Contract test for [endpoint] in tests/contract/test_[name].py
- [ ] T019 [P] [US2] Integration test for [user journey] in tests/integration/test_[name].py
### Implementation for User Story 2
- [ ] T020 [P] [US2] Create [Entity] model in src/models/[entity].py
- [ ] T021 [US2] Implement [Service] in src/services/[service].py
- [ ] T022 [US2] Implement [endpoint/feature] in src/[location]/[file].py
- [ ] T023 [US2] Integrate with User Story 1 components (if needed)
**Checkpoint**: At this point, User Stories 1 AND 2 should both work independently
---
## Phase 5: User Story 3 - [Title] (Priority: P3)
**Goal**: [Brief description of what this story delivers]
**Independent Test**: [How to verify this story works on its own]
### Tests for User Story 3 (OPTIONAL - only if tests requested) ⚠️
- [ ] T024 [P] [US3] Contract test for [endpoint] in tests/contract/test_[name].py
- [ ] T025 [P] [US3] Integration test for [user journey] in tests/integration/test_[name].py
### Implementation for User Story 3
- [ ] T026 [P] [US3] Create [Entity] model in src/models/[entity].py
- [ ] T027 [US3] Implement [Service] in src/services/[service].py
- [ ] T028 [US3] Implement [endpoint/feature] in src/[location]/[file].py
**Checkpoint**: All user stories should now be independently functional
---
[Add more user story phases as needed, following the same pattern]
---
## Phase N: Polish & Cross-Cutting Concerns
**Purpose**: Improvements that affect multiple user stories
- [ ] TXXX [P] Documentation updates in docs/
- [ ] TXXX Code cleanup and refactoring
- [ ] TXXX Performance optimization across all stories
- [ ] TXXX [P] Additional unit tests (if requested) in tests/unit/
- [ ] TXXX Security hardening
- [ ] TXXX Run quickstart.md validation
---
## Dependencies & Execution Order
### Phase Dependencies
- **Setup (Phase 1)**: No dependencies - can start immediately
- **Foundational (Phase 2)**: Depends on Setup completion - BLOCKS all user stories
- **User Stories (Phase 3+)**: All depend on Foundational phase completion
- User stories can then proceed in parallel (if staffed)
- Or sequentially in priority order (P1 → P2 → P3)
- **Polish (Final Phase)**: Depends on all desired user stories being complete
### User Story Dependencies
- **User Story 1 (P1)**: Can start after Foundational (Phase 2) - No dependencies on other stories
- **User Story 2 (P2)**: Can start after Foundational (Phase 2) - May integrate with US1 but should be independently testable
- **User Story 3 (P3)**: Can start after Foundational (Phase 2) - May integrate with US1/US2 but should be independently testable
### Within Each User Story
- Tests (if included) MUST be written and FAIL before implementation
- Models before services
- Services before endpoints
- Core implementation before integration
- Story complete before moving to next priority
### Parallel Opportunities
- All Setup tasks marked [P] can run in parallel
- All Foundational tasks marked [P] can run in parallel (within Phase 2)
- Once Foundational phase completes, all user stories can start in parallel (if team capacity allows)
- All tests for a user story marked [P] can run in parallel
- Models within a story marked [P] can run in parallel
- Different user stories can be worked on in parallel by different team members
---
## Parallel Example: User Story 1
```bash
# Launch all tests for User Story 1 together (if tests requested):
Task: "Contract test for [endpoint] in tests/contract/test_[name].py"
Task: "Integration test for [user journey] in tests/integration/test_[name].py"
# Launch all models for User Story 1 together:
Task: "Create [Entity1] model in src/models/[entity1].py"
Task: "Create [Entity2] model in src/models/[entity2].py"
```
---
## Implementation Strategy
### MVP First (User Story 1 Only)
1. Complete Phase 1: Setup
2. Complete Phase 2: Foundational (CRITICAL - blocks all stories)
3. Complete Phase 3: User Story 1
4. **STOP and VALIDATE**: Test User Story 1 independently
5. Deploy/demo if ready
### Incremental Delivery
1. Complete Setup + Foundational → Foundation ready
2. Add User Story 1 → Test independently → Deploy/Demo (MVP!)
3. Add User Story 2 → Test independently → Deploy/Demo
4. Add User Story 3 → Test independently → Deploy/Demo
5. Each story adds value without breaking previous stories
### Parallel Team Strategy
With multiple developers:
1. Team completes Setup + Foundational together
2. Once Foundational is done:
- Developer A: User Story 1
- Developer B: User Story 2
- Developer C: User Story 3
3. Stories complete and integrate independently
---
## Notes
- [P] tasks = different files, no dependencies
- [Story] label maps task to specific user story for traceability
- Each user story should be independently completable and testable
- Verify tests fail before implementing
- Commit after each task or logical group
- Stop at any checkpoint to validate story independently
- Avoid: vague tasks, same file conflicts, cross-story dependencies that break independence

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# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Project Overview
An Actix-web REST API for serving images and videos from a filesystem with automatic thumbnail generation, EXIF extraction, tag organization, and a memories feature for browsing photos by date. Uses SQLite/Diesel ORM for data persistence and ffmpeg for video processing.
## Development Commands
### Building & Running
```bash
# Build for development
cargo build
# Build for release (uses thin LTO optimization)
cargo build --release
# Run the server (requires .env file with DATABASE_URL, BASE_PATH, THUMBNAILS, VIDEO_PATH, BIND_URL, SECRET_KEY)
cargo run
# Run with specific log level
RUST_LOG=debug cargo run
```
### Testing
```bash
# Run all tests (requires BASE_PATH in .env)
cargo test
# Run specific test
cargo test test_name
# Run tests with output
cargo test -- --nocapture
```
### Database Migrations
```bash
# Install diesel CLI (one-time setup)
cargo install diesel_cli --no-default-features --features sqlite
# Create new migration
diesel migration generate migration_name
# Run migrations (also runs automatically on app startup)
diesel migration run
# Revert last migration
diesel migration revert
# Regenerate schema.rs after manual migration changes
diesel print-schema > src/database/schema.rs
```
### Code Quality
```bash
# Format code
cargo fmt
# Run clippy linter
cargo clippy
# Fix automatically fixable issues
cargo fix
```
### Utility Binaries
```bash
# Two-phase cleanup: resolve missing files and validate file types
cargo run --bin cleanup_files -- --base-path /path/to/media --database-url ./database.db
```
## Architecture Overview
### Core Components
**Layered Architecture:**
- **Startup wiring** (`main.rs`): only ~350 lines — env load, migrations, AppState, route registration, server bind. Background jobs are kicked off here but defined elsewhere.
- **HTTP Layer** (`handlers/{image,video,favorites}.rs`, `files.rs`, `tags.rs`, `faces.rs`, `memories.rs`, `ai/handlers.rs`): the route handlers, grouped by domain.
- **Background loops** (`watcher.rs`): the file-watcher tick (`watch_files`, `process_new_files`) and the orphaned-playlist cleanup (`cleanup_orphaned_playlists`). Per-tick drains are factored into `backfill.rs` (`backfill_unhashed_backlog`, `backfill_missing_date_taken`, `backfill_missing_content_hashes`, `process_face_backlog`, `build_face_candidates`).
- **Thumbnails** (`thumbnails.rs`): generation pipeline + the `IMAGE_GAUGE` / `VIDEO_GAUGE` Prometheus metrics.
- **Auth Layer** (`auth.rs`): JWT token validation, Claims extraction via FromRequest trait
- **Service Layer** (`files.rs`, `exif.rs`, `memories.rs`): Business logic for file operations and EXIF extraction
- **DAO Layer** (`database/mod.rs`): Trait-based data access (ExifDao, UserDao, FavoriteDao, TagDao)
- **Database Layer**: Diesel ORM with SQLite, schema in `database/schema.rs`
**Async Actor System (Actix):**
- `StreamActor`: Manages ffmpeg video processing lifecycle
- `VideoPlaylistManager`: Scans directories and queues videos
- `PlaylistGenerator`: Creates HLS playlists for video streaming
### Database Schema & Patterns
**Tables:**
- `users`: Authentication (id, username, password_hash)
- `favorites`: User-specific favorites (userid, path)
- `tags`: Custom labels with timestamps
- `tagged_photo`: Many-to-many photo-tag relationships
- `image_exif`: Rich metadata (file_path + 16 EXIF fields: camera, GPS, dates, exposure settings)
**DAO Pattern:**
All database access goes through trait-based DAOs (e.g., `ExifDao`, `SqliteExifDao`). Connection pooling uses `Arc<Mutex<SqliteConnection>>`. All DB operations are traced with OpenTelemetry in release builds.
**Key DAO Methods:**
- `store_exif()`, `get_exif()`, `get_exif_batch()`: EXIF CRUD operations
- `query_by_exif()`: Complex filtering by camera, GPS bounds, date ranges
- Batch operations minimize DB hits during file watching
### Multi-library data model
ImageApi supports more than one library (a library = a `(name, root_path)`
row in the `libraries` table that maps to a mounted directory tree). The
same bytes may exist under more than one library — typical case is an
"active" library plus an "archive" library that ingests files as they age
out — and the data model is designed so that derived data follows the
**bytes**, not the path, while user-managed data does the same.
**The principle.** A photo's identity is its `content_hash` (blake3, see
`src/content_hash.rs`). Anything we compute from or attach to a photo is
keyed on that hash so it survives:
- the same file appearing in a second library (backup / archive / mirror),
- the file moving between libraries (recent → archive handoff),
- the file moving within a library (re-organized rel_path),
- intra-library duplicates (same bytes at two paths).
**Table classification.** Three categories drive the keying decision:
| Category | Key | Rationale | Tables |
|---|---|---|---|
| Intrinsic to bytes | `content_hash` | Rerunning is wasted work (or LLM cost) | `face_detections` ✓, `image_exif` (target), `photo_insights` (target), `video_preview_clips` (target) |
| User intent about a photo | `content_hash` | "Tag this photo" means the bytes, not a path | `tagged_photo` (target), `favorites` (target) |
| Library administrative | `(library_id, rel_path)` | Tied to a specific filesystem location | `libraries`, `entity_photo_links`, the `rel_path` back-ref columns on hash-keyed tables |
✓ = already implemented this way. *(target)* = today still keyed on
`(library_id, rel_path)` and slated for migration. The migration adds a
nullable `content_hash` column, populates it from `image_exif` where
known, and read paths fall back to rel_path while the hash is null.
**Carrying a `rel_path` even when hash-keyed.** Hash-keyed tables retain
`(library_id, rel_path)` columns as a denormalized **back-reference**, not
as the key. This lets a single query answer "what is at this path right
now" without joining through `image_exif`, and supports the path-only
endpoints that predate the hash. `face_detections` is the reference
implementation: hash is the truth, path is a hint.
**Merge semantics on read.** When the same hash has rows under more than
one library:
- Set-valued data (tags, favorites, faces, entity links) → **union**.
- Scalar data (current insight, EXIF row, video preview clip) → earliest
`generated_at` / `created_time` wins. The historical lib1 row beats a
re-generated lib2 row, so the user's curated insight isn't shadowed by
a re-run on archive ingest.
**Write attribution.** A new tag/favorite/insight created while viewing
under lib2 binds to the bytes, not to lib2 — so it shows up under lib1
too. This is by design, but it's the most surprising rule on first
encounter; clients should not assume tags are library-scoped.
**Hash-less rows (transitional state).** During and immediately after a
new mount, `image_exif.content_hash` is being populated by
`backfill_unhashed_backlog` (capped per tick). Rules during this window:
- Writes: if the hash is known, write hash-keyed. If not, write
`(library_id, rel_path)`-keyed and let the reconciliation job collapse
duplicates once the hash lands.
- Reads: prefer hash key, fall back to `(library_id, rel_path)`.
- Reconciliation: a one-shot pass after every backfill tick collapses
rows that now share a hash, applying the merge semantics above.
Idempotent — safe to re-run.
**Library handoff (recent → archive).** When a file moves between
libraries (e.g. operator moves `~/photos/2024/IMG.nef` to the archive
mount), the file watcher sees the disappearance under lib1 and the
appearance under lib2. Hash-keyed rows don't need migration; the
`(library_id, rel_path)` back-ref columns are updated to point to the new
location. Library administrative rows (`entity_photo_links`,
`(library_id, rel_path)` rows in `image_exif` for hash-less items) are
re-keyed by the move detector, which matches a disappearance to an
appearance by `content_hash` within a configurable window.
**Orphans (source deleted while a copy survives).** When the only
`image_exif` row for a hash is deleted (file removed from disk), the
hash-keyed derived rows survive **as long as another `image_exif` row
references the same hash**. If the last reference is gone, derived rows
are eligible for GC (deferred — the GC job runs on a slow schedule so
that a brief unmount or rename doesn't wipe history).
**Stats and counts.** When reporting "how many photos do you have," count
`DISTINCT content_hash` over `image_exif`, not row count. Faces stats
already does this (`FaceDao::stats` in `src/faces.rs`); other counters
should follow suit. Numerator and denominator must live in the same
domain — see the face-stats commentary below for the cautionary tale.
**Per-library scoping when the user asks for it.** A request scoped to
`?library=N` filters the `image_exif` view to that library, and the
hash-keyed derived data is joined through that view. The user sees only
photos that have a copy under lib N, but the derived data attached to
those photos is the merged hash-keyed view. This is the answer to "show
me archive photos with their original tags."
**Operator kill switch (`libraries.enabled`).** Setting `enabled=0` on a
library is a hard pause: the watcher skips it entirely — before the
probe, before ingest, before any maintenance pass — and the orphan-GC
all-online consensus check filters disabled libraries out (they don't
keep the GC window closed). Reads / serving are unaffected; nothing
prevents `/image?path=...` from resolving against a disabled library's
root if the file is on disk. The existing `image_exif` rows for a
disabled library are **not deleted** — they continue to anchor
hash-keyed derived data, so cross-library duplicates survive the
disable. Toggle via SQL; there is intentionally no HTTP endpoint for
library mutation (single-user tool, no role / permission story).
Typical workflows: stage a new mount with `enabled=0` then flip to `1`;
quiet a flaky NAS during maintenance without disturbing the rest of
the system.
**Per-library excludes (`libraries.excluded_dirs`).** A
comma-separated column, same shape as the global `EXCLUDED_DIRS` env
var, that's applied **in union** with the env-var globals when a
walker scans this library. Use case: mount a parent directory as a
new library while a sibling library covers a child subtree, and
exclude that child subtree from the parent so the two libraries
don't double-walk and double-write `image_exif`. Two entry forms
(parsed by `memories::PathExcluder`):
- `/sub/path` — leading slash flags it as a path under the library
root. Joins to root + matches by `path.starts_with(...)`. Works
at any depth (`/photos`, `/media/2024/raw`).
- `name` — no leading slash flags it as a component name to skip
anywhere in the tree (`@eaDir`, `.thumbnails`). Single segment
only — `media/photos/a` without a leading slash never matches
anything. Hash-keyed derived
data (faces, tags, insights) is unaffected either way — those
follow the bytes — but `image_exif` row count, walker CPU, and
thumbnail disk usage all drop to 1× instead of 2× for the overlap.
Affects: file-watch ingest (`process_new_files`), thumbnail
generation, media-count gauges, the orphaned-playlist cleanup walk,
and the `/memories` endpoint. The face-detection backlog drain
inherits via `face_watch::filter_excluded`. NULL = no extras (only
the global env var applies).
**Library availability and safety.** Libraries can be on network shares
or removable media; the file watcher must not interpret a temporary
unavailability as a mass-deletion event. Every tick begins with a
**presence probe** per library: the library is considered online iff
its `root_path` exists, is readable, and a top-level scan returns at
least one expected entry (or matches a recent file-count high-water
mark within a tolerance). The probe result gates which actions are safe
to run on that library this tick:
| Action | Requires online? |
|---|---|
| Quick / full scan ingest of new files | yes |
| EXIF / face / insight backlog drains | yes — but the work runs against any online library |
| Move-handoff detection (lib1 disappearance ↔ lib2 appearance match) | **both** libraries online |
| `(library_id, rel_path)` re-keying on detected move | **both** libraries online |
| Orphan GC of hash-keyed derived data | all libraries that have *ever* held the hash must be online and confirmed-clean for two consecutive ticks |
| Reads / serving | always allowed; falls back to whichever library is online |
A library that fails the probe enters a "stale" state: writes scoped to
it are paused, its rows are flagged stale (not deleted) in
`/libraries` status, and the watcher logs at `warn` once per
state-transition (not per tick). A library that recovers re-enters the
online set automatically; no operator action required for transient
outages. The intent is that pulling a USB drive, rebooting a NAS, or
losing a VPN never triggers a destructive code path — the worst case is
that derived-data work pauses until the share returns.
The same rule constrains the move-handoff matcher: a disappearance
under lib1 only counts as a "move" if there is a matching appearance
under another **online** library within the window. A bare
disappearance with no matching appearance is treated as
"unavailable-or-deleted, defer judgment" — it does not re-key any rows
and does not enqueue GC.
**Maintenance pipeline (`src/library_maintenance.rs`).** The watcher
runs three maintenance passes per tick that together implement the
move/handoff and orphan rules:
1. **Missing-file scan** — per online library, paginated. A page of
`image_exif` rows is loaded (`IMAGE_EXIF_MISSING_SCAN_PAGE_SIZE`,
default 500), each row's `(root_path/rel_path)` is `stat()`-ed,
and confirmed-not-found rows are deleted from `image_exif`
(capped at `IMAGE_EXIF_MISSING_DELETE_CAP_PER_TICK`, default 200).
Permission/IO errors are skipped, never deleted — only `NotFound`
triggers a deletion. The cursor wraps every time a partial page
comes back, so the whole library is swept across consecutive ticks.
Skipped wholesale for Stale libraries via the per-library probe
gate at the top of the loop iteration.
2. **Back-ref refresh** — DB-only. For `face_detections`,
`tagged_photo`, and `photo_insights`: any hash-keyed row whose
`(library_id, rel_path)` no longer matches an `image_exif` row
*but whose `content_hash` does* is repointed at the surviving
`image_exif` location. Idempotent SQL; no health gate needed.
This is what makes the recent → archive handoff invisible to
read paths: when the missing-file scan retires the lib-A row,
tags/faces/insights pivot to lib-B's path before any user
notices.
3. **Orphan GC** — destructive. Hash-keyed derived rows whose
`content_hash` no longer has any `image_exif` row are eligible.
Two-tick consensus: a hash must be observed orphaned on two
consecutive ticks AND every library must be online for both. A
single Stale tick within the window cancels all pending deletes.
The pending set is held in memory (`OrphanGcState`) — restart
resets it, which only delays a delete, never causes one. Tags,
faces, and insights for orphaned hashes are deleted in one batch
per tick.
A backup library that briefly disappears, then returns within two
ticks, never loses any derived data. A move from lib-A to lib-B
without disappearance flips through pass 1 (lib-A row retired) and
pass 2 (back-refs follow), with pass 3 noting nothing because the
hash is still present in `image_exif` (lib-B's row).
**Known gap: in-place content changes (future Branch D).** The
maintenance pipeline assumes a `(library_id, rel_path)`'s bytes are
stable for as long as the file exists at that path. If a user edits
a file in place (crop, re-export) without renaming, the watcher's
quick scan walks the file (mtime is recent) but `process_new_files`
short-circuits because `(library_id, rel_path)` already has an
`image_exif` row — no re-hash, no re-EXIF, no face redetection. The
row's `content_hash` keeps pointing at the original bytes. Tags /
faces / insights stay attached to the original hash and continue to
display because the rel_path back-ref still resolves; new faces
introduced by the edit are never detected.
The right place to fix this is a **stale-content detection pass**
that compares `image_exif.last_modified` / `size_bytes` to
`fs::metadata` for rows the quick scan would otherwise skip. On
mismatch, recompute the hash, update `image_exif`, and apply the
"content branched" semantics:
- **Faces** re-run (faces are fully derived from bytes).
- **Tags** migrate to the new hash (user intent — "this photo is
vacation" survives a crop). Insights migrate forward as a
starting point and are flagged for re-generation.
- **Favorites** (when migrated to hash-keyed) follow the path /
user intent.
The interesting case is the operator who keeps an unedited copy in
the archive library and edits the local copy: post-detection, the
archive copy stays on the original hash, the local copy branches to
the new hash, and the two histories cleanly split. Apollo's
`derived.db` cache will need an invalidation hook for the changed
hash — design it alongside Branch D.
### File Processing Pipeline
**Thumbnail Generation:**
1. Startup scan: Rayon parallel walk of BASE_PATH
2. Creates 200x200 thumbnails in THUMBNAILS directory (mirrors source structure)
3. Videos: extracts frame at 3-second mark via ffmpeg
4. Images: uses `image` crate for JPEG/PNG processing
5. RAW formats (NEF/CR2/ARW/DNG/etc.): the `image` crate can't decode RAW
pixel data, so the pipeline pulls an embedded JPEG preview instead. Fast
path is `exif::read_jpeg_at_ifd` against IFD0 (PRIMARY) and IFD1
(THUMBNAIL) — covers most older bodies and DNGs. Slow-path fallback shells
out to **`exiftool`** for `PreviewImage` / `JpgFromRaw` / `OtherImage`,
which reaches MakerNote / SubIFD-hosted previews kamadak-exif can't see
(e.g. Nikon's `PreviewIFD`, where modern Nikon bodies store the full-res
review JPEG). All candidates are pooled and the largest valid JPEG wins.
See `src/exif.rs::extract_embedded_jpeg_preview`.
**File Watching:**
Runs in background thread with two-tier strategy:
- **Quick scan** (default 60s): Recently modified files only
- **Full scan** (default 3600s): Comprehensive directory check
- Batch queries EXIF DB to detect new files
- Configurable via `WATCH_QUICK_INTERVAL_SECONDS` and `WATCH_FULL_INTERVAL_SECONDS`
**Canonical date_taken pipeline (`src/date_resolver.rs`).** Every row's
`image_exif.date_taken` is populated at ingest by a four-step waterfall;
which step won is recorded in `image_exif.date_taken_source` so the
per-tick drain can re-resolve weak entries when better tools become
available, and so the UI/debug surface can answer "why did this photo
land on this date?". Order:
1. **`exif`** — kamadak-exif `DateTime` / `DateTimeOriginal`. Fast,
in-process, image-only.
2. **`exiftool`** — shell-out fallback for tags kamadak can't reach:
QuickTime/MP4 (`MediaCreateDate`, `TrackCreateDate`, `CreateDate`),
Apple's `ContentCreateDate`, MakerNote sub-IFDs. Required for
videos to land a real date. Single-file at ingest; the per-tick
drain feeds the whole batch through one `exiftool -@ -` subprocess.
Degrades silently when `exiftool` isn't on PATH (resolver caches the
"available" check via `OnceLock`).
3. **`filename`** — `extract_date_from_filename` in `memories.rs`
matches screenshot, chat-export, and timestamp-named patterns.
4. **`fs_time`** — `earliest_fs_time(metadata)` (earlier of created /
modified). Last resort.
Notable behavior change vs. the pre-2026-05 request-time logic:
**EXIF beats filename when both are present.** A photo named
`Screenshot_2014-06-01.png` whose EXIF `DateTime` is 2021 now appears
under 2021, not 2014 — on the theory that EXIF is more reliable than
import-named filenames. The reverse case (no EXIF, filename has a
date) is unchanged.
The `backfill_missing_date_taken` drain (`src/backfill.rs`) runs every
watcher tick alongside `backfill_unhashed_backlog` (also `src/backfill.rs`). It loads up to
`DATE_BACKFILL_MAX_PER_TICK` rows (default 500) where
`date_taken IS NULL` (backed by the `idx_image_exif_date_backfill`
partial index), runs the waterfall batch via `resolve_dates_batch`,
and writes results via the `backfill_date_taken` DAO method (touches
only `date_taken` + `date_taken_source` so EXIF / hash / perceptual
columns are preserved). Resolved rows — including the ones the
waterfall could only resolve via `fs_time` — are not re-eligible:
the resolver is deterministic on file bytes + filename + fs metadata,
so re-running on the same inputs lands on the same source every time.
An earlier version included `date_taken_source = 'fs_time'` in the
eligibility predicate, but with `ORDER BY id ASC LIMIT 500` it spun on
the same lowest-id rows in perpetuity and held the SQLite write lock
long enough to starve face-PATCH writers (5s busy_timeout → 500). If
a stronger tool comes online (exiftool install, new filename regex),
re-resolve out-of-band rather than re-introducing the steady-state
eligibility.
`/memories` is a single SQL query against this column
(`get_memories_in_window` in `src/database/mod.rs`), using
`strftime('%m-%d' | '%W' | '%m', date_taken, 'unixepoch', tz)` for
calendar matching with the client's timezone offset. The pre-rewrite
version stat'd every row and walked the entire library tree — at
~14k photos this took 1015 s; the rewrite is single-digit ms.
**EXIF Extraction:**
- Uses `kamadak-exif` crate
- Supports: JPEG, TIFF, RAW (NEF, CR2, CR3), HEIF/HEIC, PNG, WebP
- Extracts: camera make/model, lens, dimensions, GPS coordinates, focal length, aperture, shutter speed, ISO, date taken
- Triggered on upload and during file watching
**File Upload Behavior:**
If file exists, appends timestamp to filename (`photo_1735124234.jpg`) to preserve history without overwrites.
### Authentication Flow
**Login:**
1. POST `/login` with username/password
2. Verify with `bcrypt::verify()` against password_hash
3. Generate JWT with claims: `{ sub: user_id, exp: 5_days_from_now }`
4. Sign with HS256 using `SECRET_KEY` environment variable
**Authorization:**
All protected endpoints extract `Claims` via `FromRequest` trait implementation. Token passed as `Authorization: Bearer <token>` header.
### API Structure
**Key Endpoint Patterns:**
```rust
// Image serving & upload
GET /image?path=...&size=...&format=...
POST /image (multipart file upload)
// Metadata & EXIF
GET /image/metadata?path=...
// Advanced search with filters
GET /photos?path=...&recursive=true&sort=DateTakenDesc&camera_make=Canon&gps_lat=...&gps_lon=...&gps_radius_km=10&date_from=...&date_to=...&tag_ids=1,2,3&media_type=Photo
// Video streaming (HLS)
POST /video/generate (creates .m3u8 playlist + .ts segments)
GET /video/stream?path=... (serves playlist)
// Tags
GET /image/tags/all
POST /image/tags (add tag to file)
DELETE /image/tags (remove tag from file)
POST /image/tags/batch (bulk tag updates)
// Memories (week-based grouping)
GET /memories?path=...&recursive=true
// AI Insights
POST /insights/generate (non-agentic single-shot)
POST /insights/generate/agentic (tool-calling loop; body: { file_path, backend?, model?, ... })
GET /insights?path=...&library=...
GET /insights/models (local Ollama models + capabilities)
GET /insights/openrouter/models (curated OpenRouter allowlist)
POST /insights/rate (thumbs up/down for training data)
// Insight Chat Continuation
POST /insights/chat (single-turn reply, non-streaming)
POST /insights/chat/stream (SSE: text / tool_call / tool_result / truncated / done)
GET /insights/chat/history?path=... (rendered transcript with tool invocations)
POST /insights/chat/rewind (truncate transcript at a rendered index)
```
**Request Types:**
- `FilesRequest`: Supports complex filtering (tags, EXIF fields, GPS radius, date ranges)
- `SortType`: Shuffle, NameAsc/Desc, TagCountAsc/Desc, DateTakenAsc/Desc
### Important Patterns
**Service Builder Pattern:**
Routes are registered via composable `ServiceBuilder` trait in `service.rs`. Allows modular feature addition.
**Path Validation:**
Always use `is_valid_full_path(&base_path, &requested_path, check_exists)` to prevent directory traversal attacks.
**File Type Detection:**
Centralized in `file_types.rs` with constants `IMAGE_EXTENSIONS` and `VIDEO_EXTENSIONS`. Provides both `Path` and `DirEntry` variants for performance.
**OpenTelemetry Tracing:**
All database operations and HTTP handlers wrapped in spans. In release builds, exports to OTLP endpoint via `OTLP_OTLS_ENDPOINT`. Debug builds use basic logger.
**Memory Exclusion:**
`PathExcluder` in `memories.rs` filters out directories from memories API via `EXCLUDED_DIRS` environment variable (comma-separated paths or substring patterns). The same excluder is applied to face-detection candidates (`face_watch::filter_excluded`) so junk directories like `@eaDir` / `.thumbnails` don't burn detect calls on Apollo.
### Face detection system
ImageApi owns the face data; Apollo (sibling repo) hosts the insightface inference service. Inference is triggered automatically by the file watcher and persisted into two tables:
- `persons(id, name UNIQUE COLLATE NOCASE, cover_face_id, entity_id, created_from_tag, notes, ...)` — operator-managed, name is the user-visible identity.
- `face_detections(id, library_id, content_hash, rel_path, bbox_*, embedding BLOB, confidence, source, person_id, status, model_version, ...)` — keyed on `content_hash` so a photo duplicated across libraries is detected once. Marker rows for `status IN ('no_faces','failed')` carry NULL bbox/embedding (CHECK constraint enforces this).
**Why content_hash and not (library_id, rel_path):** ties face data to the bytes, not the path. A backup mount that copies files from the primary library naturally inherits the existing detections without re-running inference. This is the reference implementation of the multi-library data model — see "Multi-library data model" above.
**File-watch hook** (`src/watcher.rs::process_new_files`): for each photo with a populated `content_hash`, check `FaceDao::already_scanned(hash)`; if not, send bytes (or embedded JPEG preview for RAW via `exif::extract_embedded_jpeg_preview`) to Apollo's `/api/internal/faces/detect`. K=`FACE_DETECT_CONCURRENCY` (default 8) parallel calls per scan tick; Apollo serializes them via its single-worker GPU pool. `face_watch.rs` is the Tokio orchestration layer.
**Per-tick backlog drain** (`src/backfill.rs`): two passes that run on every watcher tick regardless of quick-vs-full scan:
- `backfill_unhashed_backlog` — populates `image_exif.content_hash` for photos that arrived before the hash field was retroactive. Capped by `FACE_HASH_BACKFILL_MAX_PER_TICK` (default 2000); errors don't burn the cap.
- `process_face_backlog` — runs detection on photos that have a hash but no `face_detections` row. Capped by `FACE_BACKLOG_MAX_PER_TICK` (default 64). Selected via a SQL anti-join (`FaceDao::list_unscanned_candidates`); videos and EXCLUDED_DIRS paths filtered out client-side via `face_watch::filter_excluded` so they never reach Apollo.
**Auto-bind on detection:** when a photo carries a tag whose name matches a `persons.name` (case-insensitive), the new face binds automatically iff cosine similarity to the person's existing-face mean is ≥ `FACE_AUTOBIND_MIN_COS` (default 0.4). Persons with no existing faces bind unconditionally and the new face becomes the cover.
**Manual face create** (`POST /image/faces`): crops the image to the user-supplied bbox, applies EXIF orientation via `exif::apply_orientation` (the `image` crate hands raw pre-rotation pixels — without this, manually-drawn bboxes never resolved a face on re-detection), pads to ~50% of bbox dims (RetinaFace anchor scales need ~50% face-fill at det_size=640), then calls Apollo's embed endpoint. A `force` flag lets the operator save a face the detector couldn't see (e.g. profile shots, occluded faces) — the row gets a zero-vector embedding so it's manually-bound only and won't participate in clustering.
**Rerun preserves manual rows** (`POST /image/faces/{id}/rerun`): only `source='auto'` rows are deleted before re-running detection. `already_scanned` returns true on ANY row, so a photo whose only faces are manually drawn never auto-redetects.
**Stats domain — content_hash, not file rows** (`FaceDao::stats` in `src/faces.rs`): `total_photos` counts `DISTINCT content_hash` over `image_exif` (filtered to image extensions, `content_hash IS NOT NULL`), and so do `scanned` / `with_faces` / `no_faces` / `failed` over `face_detections`. Numerator and denominator must live in the same domain — `face_detections` is keyed on content_hash, so the same JPEG present at two rel_paths or in two libraries scans once. Counting `image_exif` rows in the denominator inflated total by one per duplicate file and produced a permanent gap (e.g. 1101/1103 with nothing actually pending). Hash-less rows are excluded from total_photos while they sit in the `backfill_unhashed_backlog` queue; otherwise the bar pins below 100% for the duration of that backfill even though those rows aren't pending detection yet — they're pending hashing.
Module map:
- `src/faces.rs``FaceDao` trait + `SqliteFaceDao` impl, route handlers for `/faces/*`, `/image/faces/*`, `/persons/*`. Mirror of `tags.rs` layout.
- `src/face_watch.rs` — Tokio orchestration for the file-watch detect pass; `filter_excluded` (PathExcluder + image-extension filter), `read_image_bytes_for_detect` (RAW preview fallback).
- `src/backfill.rs` — per-tick drains (unhashed-hash, date_taken, face-backlog, etc.) called from `watcher::watch_files` and `watcher::process_new_files`.
- `src/watcher.rs` — the watcher loop itself and `process_new_files` (file walk → EXIF write → face-candidate build).
- `src/ai/face_client.rs` — HTTP client for Apollo's inference. Configured by `APOLLO_FACE_API_BASE_URL`, falls back to `APOLLO_API_BASE_URL`. Both unset → feature disabled, file-watch hook is a no-op.
- `migrations/2026-04-29-000000_add_faces/` — schema.
### Startup Sequence
1. Load `.env` file
2. Run embedded Diesel migrations
3. Spawn file watcher thread
4. Create initial thumbnails (parallel scan)
5. Generate video GIF thumbnails
6. Initialize AppState with Actix actors
7. Set up Prometheus metrics (`imageserver_image_total`, `imageserver_video_total`)
8. Scan directory for videos and queue HLS processing
9. Start HTTP server on `BIND_URL` + localhost:8088
## Testing Patterns
Tests require `BASE_PATH` environment variable. Many integration tests create temporary directories and files.
When testing database code:
- Use in-memory SQLite: `DATABASE_URL=":memory:"`
- Run migrations in test setup
- Clean up with `DROP TABLE` or use `#[serial]` from `serial_test` crate if parallel tests conflict
## Common Gotchas
**EXIF Date Parsing:**
Multiple formats supported (EXIF DateTime, ISO8601, Unix timestamp). Fallback chain attempts multiple parsers.
**Video Processing:**
ffmpeg processes run asynchronously via actors. Use `StreamActor` to track completion. HLS segments written to `VIDEO_PATH`.
**File Extensions:**
Extension detection is case-insensitive. Use `file_types.rs` helpers rather than manual string matching.
**Migration Workflow:**
After creating a migration, manually edit the SQL, then regenerate `schema.rs` with `diesel print-schema`. Migrations auto-run on startup via `embedded_migrations!()` macro.
**Path Absolutization:**
Use `path-absolutize` crate's `.absolutize()` method when converting user-provided paths to ensure they're within `BASE_PATH`.
## Required Environment Variables
```bash
DATABASE_URL=./database.db # SQLite database path
BASE_PATH=/path/to/media # Root media directory
THUMBNAILS=/path/to/thumbnails # Thumbnail storage
VIDEO_PATH=/path/to/video/hls # HLS playlist output
GIFS_DIRECTORY=/path/to/gifs # Video GIF thumbnails
BIND_URL=0.0.0.0:8080 # Server binding
CORS_ALLOWED_ORIGINS=http://localhost:3000
SECRET_KEY=your-secret-key-here # JWT signing secret
RUST_LOG=info # Log level
EXCLUDED_DIRS=/private,/archive # Comma-separated paths to exclude from memories
```
Optional:
```bash
WATCH_QUICK_INTERVAL_SECONDS=60 # Quick scan interval
WATCH_FULL_INTERVAL_SECONDS=3600 # Full scan interval
DATE_BACKFILL_MAX_PER_TICK=500 # Cap on canonical-date drain per watcher tick
OTLP_OTLS_ENDPOINT=http://... # OpenTelemetry collector (release builds)
# AI Insights Configuration
OLLAMA_PRIMARY_URL=http://desktop:11434 # Primary Ollama server (e.g., desktop)
OLLAMA_FALLBACK_URL=http://server:11434 # Fallback Ollama server (optional, always-on)
OLLAMA_PRIMARY_MODEL=nemotron-3-nano:30b # Model for primary server (default: nemotron-3-nano:30b)
OLLAMA_FALLBACK_MODEL=llama3.2:3b # Model for fallback server (optional, uses primary if not set)
OLLAMA_REQUEST_TIMEOUT_SECONDS=120 # Per-request generation timeout (default 120). Increase for slow CPU-offloaded models.
SMS_API_URL=http://localhost:8000 # SMS message API endpoint (default: localhost:8000)
SMS_API_TOKEN=your-api-token # SMS API authentication token (optional)
# Apollo Places integration (optional). When set, photo-insight enrichment
# folds the user's personal place name (Home, Work, Cabin, ...) into the
# location string fed to the LLM, and the agentic loop gains a
# `get_personal_place_at` tool. Unset = legacy Nominatim-only path.
APOLLO_API_BASE_URL=http://apollo.lan:8000 # Base URL of the sibling Apollo backend
# Face inference (optional). Apollo also hosts the insightface inference
# service; ImageApi calls it from the file-watch hook (Phase 3) and from
# the manual face-create endpoint. Falls back to APOLLO_API_BASE_URL when
# unset (typical single-Apollo deploy). Both unset = feature disabled.
APOLLO_FACE_API_BASE_URL=http://apollo.lan:8000 # Override if face service runs separately
FACE_AUTOBIND_MIN_COS=0.4 # Phase 3: cosine-sim floor for tag-name auto-bind
FACE_DETECT_CONCURRENCY=8 # Phase 3: per-scan-tick parallel detect calls
FACE_DETECT_TIMEOUT_SEC=60 # reqwest client timeout (CPU inference can be slow)
# OpenRouter (Hybrid Backend) - keeps embeddings + vision local, routes chat to OpenRouter
OPENROUTER_API_KEY=sk-or-... # Required to enable hybrid backend
OPENROUTER_DEFAULT_MODEL=anthropic/claude-sonnet-4 # Used when client doesn't pick a model
OPENROUTER_ALLOWED_MODELS=openai/gpt-4o-mini,anthropic/claude-haiku-4-5,google/gemini-2.5-flash
# Curated allowlist exposed to clients via
# GET /insights/openrouter/models. Empty = no picker.
OPENROUTER_BASE_URL=https://openrouter.ai/api/v1 # Override base URL (optional)
OPENROUTER_EMBEDDING_MODEL=openai/text-embedding-3-small # Optional, embeddings stay local today
OPENROUTER_HTTP_REFERER=https://your-site.example # Optional attribution header
OPENROUTER_APP_TITLE=ImageApi # Optional attribution header
# Insight Chat Continuation
AGENTIC_CHAT_MAX_ITERATIONS=6 # Cap on tool-calling iterations per chat turn (default 6)
```
**AI Insights Fallback Behavior:**
- Primary server is tried first with its configured model (5-second connection timeout)
- On connection failure, automatically falls back to secondary server with its model (if configured)
- If `OLLAMA_FALLBACK_MODEL` not set, uses same model as primary server on fallback
- Total request timeout is 120 seconds to accommodate slow LLM inference
- Logs indicate which server and model was used (info level) and failover attempts (warn level)
- Backwards compatible: `OLLAMA_URL` and `OLLAMA_MODEL` still supported as fallbacks
**Model Discovery:**
The `OllamaClient` provides methods to query available models:
- `OllamaClient::list_models(url)` - Returns list of all models on a server
- `OllamaClient::is_model_available(url, model_name)` - Checks if a specific model exists
This allows runtime verification of model availability before generating insights.
**Hybrid Backend (OpenRouter):**
- Per-request opt-in via `backend=hybrid` on `POST /insights/generate/agentic`.
- Local Ollama still describes the image (vision); the description is inlined
into the chat prompt and the agentic loop runs on OpenRouter.
- `request.model` (if provided) overrides `OPENROUTER_DEFAULT_MODEL` for that
call. The mobile picker reads from `OPENROUTER_ALLOWED_MODELS`.
- No live capability precheck — the operator-curated allowlist is trusted.
A bad model id surfaces as a chat-call error.
- `GET /insights/openrouter/models` returns `{ models, default_model, configured }`
for client picker UIs.
**Insight Chat Continuation:**
After an agentic insight is generated, the full `Vec<ChatMessage>` transcript is
stored in `photo_insights.training_messages` and can be continued via the
chat endpoints. The `PhotoInsightResponse.has_training_messages` flag tells
clients whether chat is available for a given insight.
- `POST /insights/chat` runs one turn of the agentic loop against the replayed
history. Body: `{ file_path, library?, user_message, model?, backend?, num_ctx?,
temperature?, top_p?, top_k?, min_p?, max_iterations?, system_prompt?, amend? }`.
`system_prompt` is a per-turn override: in append mode (default) it's applied
ephemerally — the original system message is restored before persistence so
the stored transcript keeps its baked persona. In amend mode the override
stays in place and becomes the new insight row's system message. Mirrors the
internal `annotate_system_with_budget` swap-and-restore pattern.
- `POST /insights/chat/stream` is the SSE variant — same request body, response
is `text/event-stream` with events: `iteration_start`, `text` (delta), `tool_call`,
`tool_result`, `truncated`, `done`, plus a server-emitted `error_message` on
failure. Preferred by the mobile client for live tool-chip updates.
- `GET /insights/chat/history?path=...&library=...` returns the rendered
transcript. Each assistant message carries a `tools: [{name, arguments, result,
result_truncated?}]` array with the tool invocations that led up to it. Tool
results over 2000 chars are truncated with `result_truncated: true`.
- `POST /insights/chat/rewind` truncates the transcript at a given rendered
index (drops that message + any tool-call scaffolding that preceded it + all
later turns). Index 0 is protected. Used for "try again from here" flows.
Backend routing rules (matches agentic-insight generation):
- Stored `backend` on the insight row is authoritative by default.
- `request.backend` may override per-turn. `local -> hybrid` is rejected in
v1 (would require on-the-fly visual-description rewrite); `hybrid -> local`
replays verbatim since the description is already inlined as text.
- `request.model` overrides the chat model (an Ollama id in local mode, an
OpenRouter id in hybrid mode).
Persistence:
- Append mode (default): re-serialize the full history and `UPDATE` the same
row's `training_messages`.
- Amend mode (`amend: true`): regenerate the title, insert a new insight row
via `store_insight` (auto-flips prior rows' `is_current=false`). Response
surfaces the new row's id as `amended_insight_id`.
Per-`(library_id, file_path)` async mutex (`AppState.insight_chat.chat_locks`)
serialises concurrent turns on the same insight so the JSON blob doesn't race.
Context management is a soft bound: if the serialized history exceeds
`num_ctx - 2048` tokens (cheap 4-byte/token heuristic), the oldest
assistant-tool_call + tool_result pairs are dropped until under budget. The
initial user message (with any images) and system prompt are always preserved.
The `truncated` event / flag is surfaced to the client when a drop occurred.
Configurable env:
- `AGENTIC_CHAT_MAX_ITERATIONS` — cap on tool-calling iterations per turn
(default 6). Per-request `max_iterations` is clamped to this cap.
**Apollo Places integration (optional):**
The sibling Apollo project (personal location-history viewer) owns
user-defined Places: `name + lat/lon + radius_m + description (+ optional
category)`. When `APOLLO_API_BASE_URL` is set, ImageApi queries
`/api/places/contains?lat=&lon=` to enrich the LLM prompt's location
string. See `src/ai/apollo_client.rs` and `src/ai/insight_generator.rs`:
- **Auto-enrichment** (always on when configured): the per-photo location
resolver folds the most-specific containing Place ("Home — near
Cambridge, MA" or "Home (My house in Cambridge) — near Cambridge, MA"
when a description is set) into the location field of `combine_contexts`.
Smallest-radius wins — Apollo sorts server-side, this code takes `[0]`.
- **Agentic tool** `get_personal_place_at(latitude, longitude)`: registered
alongside `reverse_geocode` only when `apollo_enabled()` returns true.
Returns "- Name [category]: description (radius N m)" lines, smallest
radius first. The tool is **deliberately narrow** — no enumerate-all
variant; auto-enrichment covers the photo-context path and the agentic
tool covers ad-hoc lat/lon questions in chat continuation.
Failure modes degrade silently to the legacy Nominatim path: 5 s timeout,
errors logged at `warn`, empty results returned. Apollo's routes are
unauthenticated (single-user, LAN-trust); add JWT auth here + on Apollo's
side if exposing beyond a trusted network.
## Dependencies of Note
### Rust crates
- **actix-web**: HTTP framework
- **diesel**: ORM for SQLite
- **jsonwebtoken**: JWT implementation
- **kamadak-exif**: EXIF parsing
- **image**: Thumbnail generation
- **walkdir**: Directory traversal
- **rayon**: Parallel processing
- **opentelemetry**: Distributed tracing
- **bcrypt**: Password hashing
- **infer**: Magic number file type detection
### External binaries (must be on `PATH`)
- **`ffmpeg`** — video thumbnail extraction (`StreamActor`, HLS pipeline) and
the HEIF/HEIC/NEF/ARW thumbnail fallback in `generate_image_thumbnail_ffmpeg`.
Required for any deploy that holds video or HEIF files.
- **`exiftool`** — optional but strongly recommended for RAW-heavy libraries.
The thumbnail pipeline shells out to it as the slow-path fallback for
embedded preview extraction (Nikon MakerNote `PreviewIFD`, Canon SubIFDs,
etc. — anything kamadak-exif's IFD0/IFD1 readers can't reach). Without
exiftool installed, RAWs whose preview lives outside IFD0/IFD1 will fall
through to ffmpeg, which often produces black thumbnails. Install via
package manager: `apt install libimage-exiftool-perl`,
`brew install exiftool`, `winget install OliverBetz.ExifTool`, or
`choco install exiftool`.

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@@ -1,38 +1,73 @@
[package]
name = "image-api"
version = "0.1.0"
version = "1.1.0"
authors = ["Cameron Cordes <cameronc.dev@gmail.com>"]
edition = "2018"
edition = "2024"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[profile.release]
lto = true
lto = "thin"
[profile.dev]
debug = "line-tables-only"
[dependencies]
actix = "0.10"
actix-web = "3"
actix-rt = "1"
actix-files = "0.5"
actix-multipart = "0.3.0"
actix = "0.13.1"
actix-web = "4"
actix-rt = "2.6"
tokio = { version = "1.42.0", features = ["default", "process", "sync", "macros", "rt-multi-thread"] }
actix-files = "0.6"
actix-cors = "0.7"
actix-multipart = "0.7.2"
actix-governor = "0.5"
futures = "0.3.5"
jsonwebtoken = "7.2.0"
jsonwebtoken = "9.3.0"
serde = "1"
serde_json = "1"
diesel = { version = "1.4.5", features = ["sqlite"] }
hmac = "0.11"
sha2 = "0.9"
diesel = { version = "2.2.10", features = ["sqlite"] }
libsqlite3-sys = "0.35"
diesel_migrations = "2.2.0"
chrono = "0.4"
clap = { version = "4.5", features = ["derive"] }
dotenv = "0.15"
bcrypt = "0.9"
image = { version = "0.23", default-features = false, features = ["jpeg", "png", "jpeg_rayon"] }
walkdir = "2"
rayon = "1.3"
notify = "4.0"
path-absolutize = "3.0.6"
log="0.4"
env_logger="0.8"
actix-web-prom = "0.5.1"
prometheus = "0.11"
lazy_static = "1.1"
bcrypt = "0.17.1"
image = { version = "0.25.5", default-features = false, features = ["jpeg", "png", "rayon", "webp", "tiff", "avif"] }
infer = "0.16"
walkdir = "2.4.0"
rayon = "1.5"
path-absolutize = "3.1"
log = "0.4"
env_logger = "0.11.5"
actix-web-prom = "0.9.0"
prometheus = "0.13"
lazy_static = "1.5"
anyhow = "1.0"
rand = "0.8.5"
opentelemetry = { version = "0.31.0", features = ["default", "metrics", "tracing"] }
opentelemetry_sdk = { version = "0.31.0", features = ["default", "rt-tokio-current-thread", "metrics"] }
opentelemetry-otlp = { version = "0.31.0", features = ["default", "metrics", "tracing", "grpc-tonic"] }
opentelemetry-stdout = "0.31.0"
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", "multipart"] }
async-stream = "0.3"
tokio-util = { version = "0.7", features = ["io"] }
bytes = "1"
urlencoding = "2.1"
zerocopy = "0.8"
ical = "0.11"
scraper = "0.20"
base64 = "0.22"
blake3 = "1.5"
image_hasher = "3.0"
bk-tree = "0.5"
async-trait = "0.1"
indicatif = "0.17"
# Windows lacks system sqlite3, so re-enable the bundled C build there.
# Linux/macOS use the system library (faster builds, smaller binary).
[target.'cfg(windows)'.dependencies]
libsqlite3-sys = { version = "0.35", features = ["bundled"] }

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pipeline {
agent {
docker {
image 'rust:1.51'
image 'rust:1.59'
args '-v "$PWD":/usr/src/image-api'
}
}

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README.md
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@@ -2,14 +2,191 @@
This is an Actix-web server for serving images and videos from a filesystem.
Upon first run it will generate thumbnails for all images and videos at `BASE_PATH`.
## Features
- Automatic thumbnail generation for images and videos
- EXIF data extraction and storage for photos
- File watching with NFS support (polling-based)
- Video streaming with HLS
- Tag-based organization
- Memories API for browsing photos by date
- **Video Wall** - Auto-generated short preview clips for videos, served via a grid view
- **AI-Powered Photo Insights** - Generate contextual insights from photos using LLMs
- **RAG-based Context Retrieval** - Semantic search over daily conversation summaries
- **Automatic Daily Summaries** - LLM-generated summaries of daily conversations with embeddings
## External Dependencies
### ffmpeg (required)
`ffmpeg` must be on `PATH`. It is used for:
- **HLS video streaming** — transcoding/segmenting source videos into `.m3u8` + `.ts` playlists
- **Video thumbnails** — extracting a frame at the 3-second mark
- **Video preview clips** — short looping previews for the Video Wall
- **HEIC / HEIF thumbnails** — decoding Apple's HEIC format (your ffmpeg build must include
`libheif`; most modern builds do)
Builds used in development: the `gyan.dev` full build on Windows, and distro `ffmpeg`
packages on Linux work fine. If HEIC thumbnails silently fail, check
`ffmpeg -formats | grep heif` to confirm HEIF support.
### RAW photo thumbnails
RAW formats (ARW, NEF, CR2, CR3, DNG, RAF, ORF, RW2, PEF, SRW, TIFF) are thumbnailed
by reading an embedded JPEG preview out of the TIFF container — no external RAW
decoder (libraw / dcraw) is involved. The pipeline tries two layers in order and
keeps the largest valid JPEG:
1. **Fast path (no extra dependency)**`kamadak-exif` reads
`JPEGInterchangeFormat` from IFD0 / IFD1 directly. Covers older bodies and
most DNGs.
2. **`exiftool` fallback (recommended for RAW-heavy libraries)** — shells out
to extract `PreviewImage` / `JpgFromRaw` / `OtherImage`, which reaches
MakerNote and SubIFD-hosted previews kamadak-exif can't see (e.g. Nikon's
`PreviewIFD`, where modern Nikon bodies stash the full-res review JPEG).
If `exiftool` isn't on `PATH` this layer is skipped silently and only the
fast-path result is used.
Install `exiftool` via your package manager:
- macOS: `brew install exiftool`
- Linux (Debian/Ubuntu): `apt install libimage-exiftool-perl`
- Windows: `winget install OliverBetz.ExifTool` or `choco install exiftool`
Files where neither layer produces a valid preview fall back to ffmpeg. Anything
that still can't be decoded is marked with a `<thumb>.unsupported` sentinel in
the thumbnail directory so we don't retry it every scan. Delete those sentinels
(and any cached black thumbnails) to force retries after a tooling upgrade.
## Environment
There are a handful of required environment variables to have the API run.
They should be defined where the binary is located or above it in an `.env` file.
- `DATABASE_URL` is a path or url to a database (currently only SQLite is tested)
- `BASE_PATH` is the root from which you want to serve images and videos
- `THUMBNAILS` is a path where generated thumbnails should be stored
- `THUMBNAILS` is a path where generated thumbnails should be stored. Thumbnails
mirror the source tree under `BASE_PATH` and keep the source's original
extension (e.g. `foo.arw` or `bar.mp4`), though the file contents are always
JPEG bytes — browsers content-sniff. Files that can't be thumbnailed by the
`image` crate, ffmpeg, or an embedded RAW preview get a zero-byte
`<thumb_path>.unsupported` sentinel in this directory so subsequent scans
skip them. Delete the `*.unsupported` files to force retries (for example
after upgrading ffmpeg or adding libheif)
- `VIDEO_PATH` is a path where HLS playlists and video parts should be stored
- `GIFS_DIRECTORY` is a path where generated video GIF thumbnails should be stored
- `BIND_URL` is the url and port to bind to (typically your own IP address)
- `SECRET_KEY` is the *hopefully* random string to sign Tokens with
- `RUST_LOG` is one of `off, error, warn, info, debug, trace`, from least to most noisy [error is default]
- `EXCLUDED_DIRS` is a comma separated list of directories to exclude from the Memories API
- `PREVIEW_CLIPS_DIRECTORY` (optional) is a path where generated video preview clips should be stored [default: `preview_clips`]
- `WATCH_QUICK_INTERVAL_SECONDS` (optional) is the interval in seconds for quick file scans [default: 60]
- `WATCH_FULL_INTERVAL_SECONDS` (optional) is the interval in seconds for full file scans [default: 3600]
### AI Insights Configuration (Optional)
The following environment variables configure AI-powered photo insights and daily conversation summaries:
#### Ollama Configuration
- `OLLAMA_PRIMARY_URL` - Primary Ollama server URL [default: `http://localhost:11434`]
- Example: `http://desktop:11434` (your main/powerful server)
- `OLLAMA_FALLBACK_URL` - Fallback Ollama server URL (optional)
- Example: `http://server:11434` (always-on backup server)
- `OLLAMA_PRIMARY_MODEL` - Model to use on primary server [default: `nemotron-3-nano:30b`]
- Example: `nemotron-3-nano:30b`, `llama3.2:3b`, etc.
- `OLLAMA_FALLBACK_MODEL` - Model to use on fallback server (optional)
- If not set, uses `OLLAMA_PRIMARY_MODEL` on fallback server
**Legacy Variables** (still supported):
- `OLLAMA_URL` - Used if `OLLAMA_PRIMARY_URL` not set
- `OLLAMA_MODEL` - Used if `OLLAMA_PRIMARY_MODEL` not set
#### OpenRouter Configuration (Hybrid Backend)
The hybrid agentic backend keeps embeddings + vision local (Ollama) while routing
chat + tool-calling to OpenRouter. Enabled per-request when the client sends
`backend=hybrid`.
- `OPENROUTER_API_KEY` - OpenRouter API key. Required to enable the hybrid backend.
- `OPENROUTER_DEFAULT_MODEL` - Model id used when the client doesn't specify one
[default: `anthropic/claude-sonnet-4`]
- Example: `openai/gpt-4o-mini`, `google/gemini-2.5-flash`
- `OPENROUTER_ALLOWED_MODELS` - Comma-separated curated allowlist exposed to
clients via `GET /insights/openrouter/models`. The mobile picker shows only
these. Empty/unset = no picker, server default is used.
- Example: `openai/gpt-4o-mini,anthropic/claude-haiku-4-5,google/gemini-2.5-flash`
- `OPENROUTER_BASE_URL` - Override base URL [default: `https://openrouter.ai/api/v1`]
- `OPENROUTER_EMBEDDING_MODEL` - Embedding model for OpenRouter
[default: `openai/text-embedding-3-small`]. Only used if/when embeddings are
routed through OpenRouter (currently embeddings stay local).
- `OPENROUTER_HTTP_REFERER` - Optional `HTTP-Referer` for OpenRouter attribution
- `OPENROUTER_APP_TITLE` - Optional `X-Title` for OpenRouter attribution
Capability checks are skipped for the curated allowlist — bad model ids surface
as a 4xx from the chat call. Pick tool-capable models.
#### SMS API Configuration
- `SMS_API_URL` - URL to SMS message API [default: `http://localhost:8000`]
- Used to fetch conversation data for context in insights
- `SMS_API_TOKEN` - Authentication token for SMS API (optional)
#### Agentic Insight Generation
- `AGENTIC_MAX_ITERATIONS` - Maximum tool-call iterations per agentic insight request [default: `10`]
- Controls how many times the model can invoke tools before being forced to produce a final answer
- Increase for more thorough context gathering; decrease to limit response time
#### Insight Chat Continuation
After an agentic insight is generated, the conversation can be continued. Endpoints:
- `POST /insights/chat` — single-turn reply (non-streaming)
- `POST /insights/chat/stream` — SSE variant with live `text` deltas and
`tool_call` / `tool_result` events. Mobile client uses this.
- `GET /insights/chat/history?path=...&library=...` — rendered transcript;
each assistant message carries a `tools: [{name, arguments, result}]` array
- `POST /insights/chat/rewind` — truncate transcript at a rendered index
(drops that message + any preceding tool scaffolding + later turns). Used
for "try again from here" flows. The initial user message is protected.
Amend mode (`amend: true` in the chat request body) regenerates the insight's
title and inserts a new row instead of appending to the existing transcript,
so you can rewrite the saved summary from within chat.
- `AGENTIC_CHAT_MAX_ITERATIONS` - Cap on tool-calling iterations per chat turn [default: `6`]
- Per-request `max_iterations` (when sent by the client) is clamped to this cap
#### Fallback Behavior
- Primary server is tried first with 5-second connection timeout
- On failure, automatically falls back to secondary server (if configured)
- Total request timeout is 120 seconds to accommodate LLM inference
- Logs indicate which server/model was used and any failover attempts
#### Daily Summary Generation
Daily conversation summaries are generated automatically on server startup. Configure in `src/main.rs`:
- Date range for summary generation
- Contacts to process
- Model version used for embeddings: `nomic-embed-text:v1.5`
### Apollo + Face Recognition (Optional)
Apollo (sibling project) hosts both the Places API and the local insightface
inference service. Both integrations are optional and degrade gracefully when
unset.
- `APOLLO_API_BASE_URL` - Base URL of the sibling Apollo backend.
- When set, photo-insight enrichment folds the user's personal place name
(Home, Work, Cabin, ...) into the location string, and the agentic loop
gains a `get_personal_place_at` tool. Unset = legacy Nominatim-only path.
- `APOLLO_FACE_API_BASE_URL` - Base URL for the face-detection service.
- Falls back to `APOLLO_API_BASE_URL` when unset (typical single-Apollo
deploy). Both unset = face feature disabled (file-watch hook and
manual-face endpoints short-circuit silently).
- `FACE_AUTOBIND_MIN_COS` (Phase 3) - Cosine-sim floor for auto-binding a
detected face to an existing same-named person via people-tag bootstrap
[default: `0.4`].
- `FACE_DETECT_CONCURRENCY` (Phase 3) - Per-scan-tick concurrent detect
calls fired by the file watcher [default: `8`]. Apollo serializes them
via its single-worker GPU pool.
- `FACE_DETECT_TIMEOUT_SEC` - reqwest client timeout per detect call
[default: `60`]. CPU inference on a backlog can take many seconds.
- `FACE_BACKLOG_MAX_PER_TICK` - Cap on the per-tick backlog drain (photos
with a content_hash but no face_detections row) [default: `64`]. Runs
every watcher tick regardless of quick-vs-full scan, so the unscanned
set drains independently of the file walk.
- `FACE_HASH_BACKFILL_MAX_PER_TICK` - Cap on the per-tick content_hash
backfill (photos that were registered before the hash field was
populated retroactively) [default: `2000`]. Errors don't burn the cap;
only successful hashes count.

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DROP TABLE tags;
DROP TABLE tagged_photo;

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CREATE TABLE tags (
id INTEGER PRIMARY KEY NOT NULL,
name TEXT NOT NULL,
created_time BIGINT NOT NULL
);
CREATE TABLE tagged_photo (
id INTEGER PRIMARY KEY NOT NULL,
photo_name TEXT NOT NULL,
tag_id INTEGER NOT NULL,
created_time BIGINT NOT NULL,
CONSTRAINT tagid FOREIGN KEY (tag_id) REFERENCES tags (id) ON DELETE CASCADE ON UPDATE CASCADE
);

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DROP INDEX IF EXISTS idx_image_exif_file_path;
DROP TABLE IF EXISTS image_exif;

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CREATE TABLE image_exif (
id INTEGER PRIMARY KEY NOT NULL,
file_path TEXT NOT NULL UNIQUE,
-- Camera Information
camera_make TEXT,
camera_model TEXT,
lens_model TEXT,
-- Image Properties
width INTEGER,
height INTEGER,
orientation INTEGER,
-- GPS Coordinates
gps_latitude REAL,
gps_longitude REAL,
gps_altitude REAL,
-- Capture Settings
focal_length REAL,
aperture REAL,
shutter_speed TEXT,
iso INTEGER,
date_taken BIGINT,
-- Housekeeping
created_time BIGINT NOT NULL,
last_modified BIGINT NOT NULL
);
CREATE INDEX idx_image_exif_file_path ON image_exif(file_path);

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-- Rollback indexes
DROP INDEX IF EXISTS idx_favorites_userid;
DROP INDEX IF EXISTS idx_favorites_path;
DROP INDEX IF EXISTS idx_tags_name;
DROP INDEX IF EXISTS idx_tagged_photo_photo_name;
DROP INDEX IF EXISTS idx_tagged_photo_tag_id;
DROP INDEX IF EXISTS idx_image_exif_camera;
DROP INDEX IF EXISTS idx_image_exif_gps;

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-- Add indexes for improved query performance
-- Favorites table indexes
CREATE INDEX IF NOT EXISTS idx_favorites_userid ON favorites(userid);
CREATE INDEX IF NOT EXISTS idx_favorites_path ON favorites(path);
-- Tags table indexes
CREATE INDEX IF NOT EXISTS idx_tags_name ON tags(name);
-- Tagged photos indexes
CREATE INDEX IF NOT EXISTS idx_tagged_photo_photo_name ON tagged_photo(photo_name);
CREATE INDEX IF NOT EXISTS idx_tagged_photo_tag_id ON tagged_photo(tag_id);
-- EXIF table indexes (date_taken already has index from previous migration)
-- Adding composite index for common EXIF queries
CREATE INDEX IF NOT EXISTS idx_image_exif_camera ON image_exif(camera_make, camera_model);
CREATE INDEX IF NOT EXISTS idx_image_exif_gps ON image_exif(gps_latitude, gps_longitude);

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-- Rollback unique constraint on favorites
DROP INDEX IF EXISTS idx_favorites_unique;

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-- Add unique constraint to prevent duplicate favorites per user
-- First, remove any existing duplicates (keep the oldest one)
DELETE FROM favorites
WHERE rowid NOT IN (
SELECT MIN(rowid)
FROM favorites
GROUP BY userid, path
);
-- Add unique index to enforce constraint
CREATE UNIQUE INDEX idx_favorites_unique ON favorites(userid, path);

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-- Remove date_taken index
DROP INDEX IF EXISTS idx_image_exif_date_taken;

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-- Add index on date_taken for efficient date range queries
CREATE INDEX IF NOT EXISTS idx_image_exif_date_taken ON image_exif(date_taken);

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-- Rollback AI insights table
DROP INDEX IF EXISTS idx_photo_insights_path;
DROP TABLE IF EXISTS photo_insights;

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-- AI-generated insights for individual photos
CREATE TABLE IF NOT EXISTS photo_insights (
id INTEGER PRIMARY KEY NOT NULL,
file_path TEXT NOT NULL UNIQUE, -- Full path to the photo
title TEXT NOT NULL, -- "At the beach with Sarah"
summary TEXT NOT NULL, -- 2-3 sentence description
generated_at BIGINT NOT NULL,
model_version TEXT NOT NULL
);
CREATE INDEX IF NOT EXISTS idx_photo_insights_path ON photo_insights(file_path);

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DROP TABLE daily_conversation_summaries;

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-- Daily conversation summaries for improved RAG quality
-- Each row = one day's conversation with a contact, summarized by LLM and embedded
CREATE TABLE daily_conversation_summaries (
id INTEGER PRIMARY KEY NOT NULL,
date TEXT NOT NULL, -- ISO date "2024-08-15"
contact TEXT NOT NULL, -- Contact name
summary TEXT NOT NULL, -- LLM-generated 3-5 sentence summary
message_count INTEGER NOT NULL, -- Number of messages in this day
embedding BLOB NOT NULL, -- 768-dim vector of the summary
created_at BIGINT NOT NULL, -- When this summary was generated
model_version TEXT NOT NULL, -- "nomic-embed-text:v1.5"
UNIQUE(date, contact)
);
-- Indexes for efficient querying
CREATE INDEX idx_daily_summaries_date ON daily_conversation_summaries(date);
CREATE INDEX idx_daily_summaries_contact ON daily_conversation_summaries(contact);
CREATE INDEX idx_daily_summaries_date_contact ON daily_conversation_summaries(date, contact);

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DROP TABLE IF EXISTS calendar_events;

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CREATE TABLE calendar_events (
id INTEGER PRIMARY KEY NOT NULL,
event_uid TEXT,
summary TEXT NOT NULL,
description TEXT,
location TEXT,
start_time BIGINT NOT NULL,
end_time BIGINT NOT NULL,
all_day BOOLEAN NOT NULL DEFAULT 0,
organizer TEXT,
attendees TEXT,
embedding BLOB,
created_at BIGINT NOT NULL,
source_file TEXT,
UNIQUE(event_uid, start_time)
);
CREATE INDEX idx_calendar_start_time ON calendar_events(start_time);
CREATE INDEX idx_calendar_end_time ON calendar_events(end_time);
CREATE INDEX idx_calendar_time_range ON calendar_events(start_time, end_time);

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DROP TABLE IF EXISTS location_history;

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CREATE TABLE location_history (
id INTEGER PRIMARY KEY NOT NULL,
timestamp BIGINT NOT NULL,
latitude REAL NOT NULL,
longitude REAL NOT NULL,
accuracy INTEGER,
activity TEXT,
activity_confidence INTEGER,
place_name TEXT,
place_category TEXT,
embedding BLOB,
created_at BIGINT NOT NULL,
source_file TEXT,
UNIQUE(timestamp, latitude, longitude)
);
CREATE INDEX idx_location_timestamp ON location_history(timestamp);
CREATE INDEX idx_location_coords ON location_history(latitude, longitude);
CREATE INDEX idx_location_activity ON location_history(activity);

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DROP TABLE IF EXISTS search_history;

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CREATE TABLE search_history (
id INTEGER PRIMARY KEY NOT NULL,
timestamp BIGINT NOT NULL,
query TEXT NOT NULL,
search_engine TEXT,
embedding BLOB NOT NULL,
created_at BIGINT NOT NULL,
source_file TEXT,
UNIQUE(timestamp, query)
);
CREATE INDEX idx_search_timestamp ON search_history(timestamp);
CREATE INDEX idx_search_query ON search_history(query);

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-- Revert search performance optimization indexes
DROP INDEX IF EXISTS idx_image_exif_date_path;
DROP INDEX IF EXISTS idx_tagged_photo_count;

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-- Add composite indexes for search performance optimization
-- This migration addresses N+1 query issues and enables database-level sorting
-- Covering index for date-sorted queries (supports ORDER BY + pagination)
-- Enables efficient date-based sorting without loading all files into memory
CREATE INDEX IF NOT EXISTS idx_image_exif_date_path
ON image_exif(date_taken DESC, file_path);
-- Optimize batch tag count queries with GROUP BY
-- Reduces N individual queries to a single batch query
CREATE INDEX IF NOT EXISTS idx_tagged_photo_count
ON tagged_photo(photo_name, tag_id);
-- Update query planner statistics to optimize query execution
ANALYZE;

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DROP TABLE IF EXISTS video_preview_clips;

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CREATE TABLE video_preview_clips (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
file_path TEXT NOT NULL UNIQUE,
status TEXT NOT NULL DEFAULT 'pending',
duration_seconds REAL,
file_size_bytes INTEGER,
error_message TEXT,
created_at TEXT NOT NULL,
updated_at TEXT NOT NULL
);
CREATE INDEX idx_preview_clips_file_path ON video_preview_clips(file_path);
CREATE INDEX idx_preview_clips_status ON video_preview_clips(status);

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-- Restore original schema, retaining only the current insight per file.
CREATE TABLE photo_insights_old (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
file_path TEXT NOT NULL UNIQUE,
title TEXT NOT NULL,
summary TEXT NOT NULL,
generated_at BIGINT NOT NULL,
model_version TEXT NOT NULL
);
INSERT INTO photo_insights_old (id, file_path, title, summary, generated_at, model_version)
SELECT id, file_path, title, summary, generated_at, model_version
FROM photo_insights
WHERE is_current = 1;
DROP TABLE photo_insights;
ALTER TABLE photo_insights_old RENAME TO photo_insights;
CREATE INDEX IF NOT EXISTS idx_photo_insights_path ON photo_insights(file_path);

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-- Convert photo_insights to an append-only history table.
-- SQLite cannot drop a UNIQUE constraint via ALTER TABLE, so we recreate the table.
-- This preserves existing insight IDs so that future entity_facts.source_insight_id
-- FK references remain valid.
CREATE TABLE photo_insights_new (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
file_path TEXT NOT NULL,
title TEXT NOT NULL,
summary TEXT NOT NULL,
generated_at BIGINT NOT NULL,
model_version TEXT NOT NULL,
is_current BOOLEAN NOT NULL DEFAULT 0
);
-- Migrate existing rows; mark them all as current (one row per path currently).
INSERT INTO photo_insights_new (id, file_path, title, summary, generated_at, model_version, is_current)
SELECT id, file_path, title, summary, generated_at, model_version, 1
FROM photo_insights;
DROP TABLE photo_insights;
ALTER TABLE photo_insights_new RENAME TO photo_insights;
CREATE INDEX idx_photo_insights_file_path ON photo_insights(file_path);
CREATE INDEX idx_photo_insights_current ON photo_insights(file_path, is_current);

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DROP TABLE IF EXISTS entity_photo_links;
DROP TABLE IF EXISTS entity_facts;
DROP TABLE IF EXISTS entities;

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-- Entity-relationship knowledge memory tables.
-- Entities are the nodes (people, places, events, things).
-- entity_facts are typed claims about or between entities.
-- entity_photo_links connect entities to specific photos.
CREATE TABLE entities (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
name TEXT NOT NULL,
entity_type TEXT NOT NULL, -- 'person' | 'place' | 'event' | 'thing'
description TEXT NOT NULL DEFAULT '',
embedding BLOB, -- 768-dim f32 vector; nullable if embedding service was unavailable
confidence REAL NOT NULL DEFAULT 0.5,
status TEXT NOT NULL DEFAULT 'active', -- 'active' | 'reviewed' | 'rejected'
created_at BIGINT NOT NULL,
updated_at BIGINT NOT NULL,
UNIQUE(name, entity_type)
);
CREATE INDEX idx_entities_type ON entities(entity_type);
CREATE INDEX idx_entities_status ON entities(status);
CREATE INDEX idx_entities_name ON entities(name);
CREATE TABLE entity_facts (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
subject_entity_id INTEGER NOT NULL,
predicate TEXT NOT NULL,
object_entity_id INTEGER, -- nullable: entity-to-entity relationship target
object_value TEXT, -- nullable: free-text attribute value
source_photo TEXT, -- photo path that prompted extraction (injected server-side)
source_insight_id INTEGER, -- backfilled after insight is stored
confidence REAL NOT NULL DEFAULT 0.6,
status TEXT NOT NULL DEFAULT 'active', -- 'active' | 'reviewed' | 'rejected'
created_at BIGINT NOT NULL,
CONSTRAINT fk_ef_subject FOREIGN KEY (subject_entity_id) REFERENCES entities(id) ON DELETE CASCADE,
CONSTRAINT fk_ef_object FOREIGN KEY (object_entity_id) REFERENCES entities(id) ON DELETE SET NULL,
CONSTRAINT fk_ef_insight FOREIGN KEY (source_insight_id) REFERENCES photo_insights(id) ON DELETE SET NULL,
CHECK (object_entity_id IS NOT NULL OR object_value IS NOT NULL)
);
CREATE INDEX idx_entity_facts_subject ON entity_facts(subject_entity_id);
CREATE INDEX idx_entity_facts_predicate ON entity_facts(predicate);
CREATE INDEX idx_entity_facts_status ON entity_facts(status);
CREATE INDEX idx_entity_facts_source_photo ON entity_facts(source_photo);
CREATE TABLE entity_photo_links (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
entity_id INTEGER NOT NULL,
file_path TEXT NOT NULL,
role TEXT NOT NULL, -- 'subject' | 'location' | 'event' | 'thing'
CONSTRAINT fk_epl_entity FOREIGN KEY (entity_id) REFERENCES entities(id) ON DELETE CASCADE,
UNIQUE(entity_id, file_path, role)
);
CREATE INDEX idx_entity_photo_links_entity ON entity_photo_links(entity_id);
CREATE INDEX idx_entity_photo_links_photo ON entity_photo_links(file_path);

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-- SQLite doesn't support DROP COLUMN directly, so we recreate the table
CREATE TABLE photo_insights_backup AS SELECT id, file_path, title, summary, generated_at, model_version, is_current FROM photo_insights;
DROP TABLE photo_insights;
CREATE TABLE photo_insights (
id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT,
file_path TEXT NOT NULL,
title TEXT NOT NULL,
summary TEXT NOT NULL,
generated_at BIGINT NOT NULL,
model_version TEXT NOT NULL,
is_current BOOLEAN NOT NULL DEFAULT TRUE
);
INSERT INTO photo_insights SELECT * FROM photo_insights_backup;
DROP TABLE photo_insights_backup;

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ALTER TABLE photo_insights ADD COLUMN training_messages TEXT;
ALTER TABLE photo_insights ADD COLUMN approved BOOLEAN;

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-- Revert multi-library support.
-- Drops library_id/content_hash/size_bytes, renames rel_path back to the
-- original column names, and drops the libraries table. Rows originally
-- from non-primary libraries (id > 1) would be orphaned, so the rollback
-- keeps only rows from library_id=1.
PRAGMA foreign_keys=OFF;
-- tagged_photo: rel_path → photo_name.
DROP INDEX IF EXISTS idx_tagged_photo_relpath_tag;
DROP INDEX IF EXISTS idx_tagged_photo_rel_path;
ALTER TABLE tagged_photo RENAME COLUMN rel_path TO photo_name;
CREATE INDEX IF NOT EXISTS idx_tagged_photo_photo_name ON tagged_photo(photo_name);
CREATE INDEX IF NOT EXISTS idx_tagged_photo_count ON tagged_photo(photo_name, tag_id);
-- favorites: rel_path → path.
DROP INDEX IF EXISTS idx_favorites_unique;
DROP INDEX IF EXISTS idx_favorites_rel_path;
ALTER TABLE favorites RENAME COLUMN rel_path TO path;
CREATE INDEX IF NOT EXISTS idx_favorites_path ON favorites(path);
CREATE UNIQUE INDEX IF NOT EXISTS idx_favorites_unique ON favorites(userid, path);
-- video_preview_clips: drop library_id, rel_path → file_path.
CREATE TABLE video_preview_clips_old (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
file_path TEXT NOT NULL UNIQUE,
status TEXT NOT NULL DEFAULT 'pending',
duration_seconds REAL,
file_size_bytes INTEGER,
error_message TEXT,
created_at TEXT NOT NULL,
updated_at TEXT NOT NULL
);
INSERT INTO video_preview_clips_old (
id, file_path, status, duration_seconds, file_size_bytes,
error_message, created_at, updated_at
)
SELECT
id, rel_path, status, duration_seconds, file_size_bytes,
error_message, created_at, updated_at
FROM video_preview_clips
WHERE library_id = 1;
DROP TABLE video_preview_clips;
ALTER TABLE video_preview_clips_old RENAME TO video_preview_clips;
CREATE INDEX idx_preview_clips_file_path ON video_preview_clips(file_path);
CREATE INDEX idx_preview_clips_status ON video_preview_clips(status);
-- entity_photo_links: drop library_id, rel_path → file_path.
CREATE TABLE entity_photo_links_old (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
entity_id INTEGER NOT NULL,
file_path TEXT NOT NULL,
role TEXT NOT NULL,
CONSTRAINT fk_epl_entity FOREIGN KEY (entity_id) REFERENCES entities(id) ON DELETE CASCADE,
UNIQUE(entity_id, file_path, role)
);
INSERT INTO entity_photo_links_old (id, entity_id, file_path, role)
SELECT id, entity_id, rel_path, role
FROM entity_photo_links
WHERE library_id = 1;
DROP TABLE entity_photo_links;
ALTER TABLE entity_photo_links_old RENAME TO entity_photo_links;
CREATE INDEX idx_entity_photo_links_entity ON entity_photo_links(entity_id);
CREATE INDEX idx_entity_photo_links_photo ON entity_photo_links(file_path);
-- photo_insights: drop library_id, rel_path → file_path.
CREATE TABLE photo_insights_old (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
file_path TEXT NOT NULL,
title TEXT NOT NULL,
summary TEXT NOT NULL,
generated_at BIGINT NOT NULL,
model_version TEXT NOT NULL,
is_current BOOLEAN NOT NULL DEFAULT 0,
training_messages TEXT,
approved BOOLEAN
);
INSERT INTO photo_insights_old (
id, file_path, title, summary, generated_at, model_version, is_current,
training_messages, approved
)
SELECT
id, rel_path, title, summary, generated_at, model_version, is_current,
training_messages, approved
FROM photo_insights
WHERE library_id = 1;
DROP TABLE photo_insights;
ALTER TABLE photo_insights_old RENAME TO photo_insights;
CREATE INDEX idx_photo_insights_file_path ON photo_insights(file_path);
CREATE INDEX idx_photo_insights_current ON photo_insights(file_path, is_current);
-- image_exif: drop library_id/content_hash/size_bytes, rel_path → file_path.
CREATE TABLE image_exif_old (
id INTEGER PRIMARY KEY NOT NULL,
file_path TEXT NOT NULL UNIQUE,
camera_make TEXT,
camera_model TEXT,
lens_model TEXT,
width INTEGER,
height INTEGER,
orientation INTEGER,
gps_latitude REAL,
gps_longitude REAL,
gps_altitude REAL,
focal_length REAL,
aperture REAL,
shutter_speed TEXT,
iso INTEGER,
date_taken BIGINT,
created_time BIGINT NOT NULL,
last_modified BIGINT NOT NULL
);
INSERT INTO image_exif_old (
id, file_path,
camera_make, camera_model, lens_model,
width, height, orientation,
gps_latitude, gps_longitude, gps_altitude,
focal_length, aperture, shutter_speed, iso, date_taken,
created_time, last_modified
)
SELECT
id, rel_path,
camera_make, camera_model, lens_model,
width, height, orientation,
gps_latitude, gps_longitude, gps_altitude,
focal_length, aperture, shutter_speed, iso, date_taken,
created_time, last_modified
FROM image_exif
WHERE library_id = 1;
DROP TABLE image_exif;
ALTER TABLE image_exif_old RENAME TO image_exif;
CREATE INDEX idx_image_exif_file_path ON image_exif(file_path);
CREATE INDEX idx_image_exif_camera ON image_exif(camera_make, camera_model);
CREATE INDEX idx_image_exif_gps ON image_exif(gps_latitude, gps_longitude);
CREATE INDEX idx_image_exif_date_taken ON image_exif(date_taken);
CREATE INDEX idx_image_exif_date_path ON image_exif(date_taken DESC, file_path);
-- Finally, drop the libraries registry.
DROP TABLE libraries;
PRAGMA foreign_keys=ON;
ANALYZE;

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@@ -0,0 +1,216 @@
-- Multi-library support.
-- Adds `libraries` registry table and a `library_id` column on per-instance
-- metadata tables. Renames `file_path` / `photo_name` to `rel_path` for
-- semantic clarity (values already stored relative to BASE_PATH).
-- Adds `content_hash` + `size_bytes` to `image_exif` to support
-- content-based dedup of thumbnails and HLS output across libraries.
--
-- SQLite cannot alter column constraints in place, so per-instance tables
-- are recreated following the idiom established in
-- 2026-04-02-000000_photo_insights_history/up.sql. Existing row `id`s are
-- preserved so foreign keys (entity_facts.source_insight_id, etc.) remain
-- valid after migration.
PRAGMA foreign_keys=OFF;
-- ---------------------------------------------------------------------------
-- 1. Libraries registry.
-- Seeded with a placeholder for the primary library; AppState patches
-- `root_path` from the BASE_PATH env var on first boot. Subsequent
-- prod-to-dev DB syncs update this row via a single SQL UPDATE.
-- ---------------------------------------------------------------------------
CREATE TABLE libraries (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
name TEXT NOT NULL UNIQUE,
root_path TEXT NOT NULL,
created_at BIGINT NOT NULL
);
INSERT INTO libraries (id, name, root_path, created_at)
VALUES (1, 'main', 'BASE_PATH_PLACEHOLDER', strftime('%s','now'));
-- ---------------------------------------------------------------------------
-- 2. image_exif: + library_id, file_path → rel_path, + content_hash/size_bytes.
-- ---------------------------------------------------------------------------
CREATE TABLE image_exif_new (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
library_id INTEGER NOT NULL REFERENCES libraries(id),
rel_path TEXT NOT NULL,
-- Camera information
camera_make TEXT,
camera_model TEXT,
lens_model TEXT,
-- Image properties
width INTEGER,
height INTEGER,
orientation INTEGER,
-- GPS
gps_latitude REAL,
gps_longitude REAL,
gps_altitude REAL,
-- Capture settings
focal_length REAL,
aperture REAL,
shutter_speed TEXT,
iso INTEGER,
date_taken BIGINT,
-- Housekeeping
created_time BIGINT NOT NULL,
last_modified BIGINT NOT NULL,
-- Content identity (backfilled by the `backfill_hashes` binary and by the watcher for new files)
content_hash TEXT,
size_bytes BIGINT,
UNIQUE(library_id, rel_path)
);
INSERT INTO image_exif_new (
id, library_id, rel_path,
camera_make, camera_model, lens_model,
width, height, orientation,
gps_latitude, gps_longitude, gps_altitude,
focal_length, aperture, shutter_speed, iso, date_taken,
created_time, last_modified
)
SELECT
id, 1, file_path,
camera_make, camera_model, lens_model,
width, height, orientation,
gps_latitude, gps_longitude, gps_altitude,
focal_length, aperture, shutter_speed, iso, date_taken,
created_time, last_modified
FROM image_exif;
DROP TABLE image_exif;
ALTER TABLE image_exif_new RENAME TO image_exif;
CREATE INDEX idx_image_exif_rel_path ON image_exif(rel_path);
CREATE INDEX idx_image_exif_camera ON image_exif(camera_make, camera_model);
CREATE INDEX idx_image_exif_gps ON image_exif(gps_latitude, gps_longitude);
CREATE INDEX idx_image_exif_date_taken ON image_exif(date_taken);
CREATE INDEX idx_image_exif_date_path ON image_exif(date_taken DESC, rel_path);
CREATE INDEX idx_image_exif_lib_date ON image_exif(library_id, date_taken);
CREATE INDEX idx_image_exif_content_hash ON image_exif(content_hash);
-- ---------------------------------------------------------------------------
-- 3. photo_insights: + library_id, file_path → rel_path.
-- Preserve `id` so entity_facts.source_insight_id FKs remain valid.
-- ---------------------------------------------------------------------------
CREATE TABLE photo_insights_new (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
library_id INTEGER NOT NULL REFERENCES libraries(id),
rel_path TEXT NOT NULL,
title TEXT NOT NULL,
summary TEXT NOT NULL,
generated_at BIGINT NOT NULL,
model_version TEXT NOT NULL,
is_current BOOLEAN NOT NULL DEFAULT 0,
training_messages TEXT,
approved BOOLEAN
);
INSERT INTO photo_insights_new (
id, library_id, rel_path, title, summary, generated_at, model_version,
is_current, training_messages, approved
)
SELECT
id, 1, file_path, title, summary, generated_at, model_version,
is_current, training_messages, approved
FROM photo_insights;
DROP TABLE photo_insights;
ALTER TABLE photo_insights_new RENAME TO photo_insights;
CREATE INDEX idx_photo_insights_rel_path ON photo_insights(rel_path);
CREATE INDEX idx_photo_insights_current ON photo_insights(library_id, rel_path, is_current);
-- ---------------------------------------------------------------------------
-- 4. entity_photo_links: + library_id, file_path → rel_path.
-- Preserves entity FK; UNIQUE now includes library_id to allow the same
-- rel_path to link entities in multiple libraries independently.
-- ---------------------------------------------------------------------------
CREATE TABLE entity_photo_links_new (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
entity_id INTEGER NOT NULL,
library_id INTEGER NOT NULL REFERENCES libraries(id),
rel_path TEXT NOT NULL,
role TEXT NOT NULL,
CONSTRAINT fk_epl_entity FOREIGN KEY (entity_id) REFERENCES entities(id) ON DELETE CASCADE,
UNIQUE(entity_id, library_id, rel_path, role)
);
INSERT INTO entity_photo_links_new (id, entity_id, library_id, rel_path, role)
SELECT id, entity_id, 1, file_path, role FROM entity_photo_links;
DROP TABLE entity_photo_links;
ALTER TABLE entity_photo_links_new RENAME TO entity_photo_links;
CREATE INDEX idx_entity_photo_links_entity ON entity_photo_links(entity_id);
CREATE INDEX idx_entity_photo_links_photo ON entity_photo_links(library_id, rel_path);
-- ---------------------------------------------------------------------------
-- 5. video_preview_clips: + library_id, file_path → rel_path.
-- ---------------------------------------------------------------------------
CREATE TABLE video_preview_clips_new (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
library_id INTEGER NOT NULL REFERENCES libraries(id),
rel_path TEXT NOT NULL,
status TEXT NOT NULL DEFAULT 'pending',
duration_seconds REAL,
file_size_bytes INTEGER,
error_message TEXT,
created_at TEXT NOT NULL,
updated_at TEXT NOT NULL,
UNIQUE(library_id, rel_path)
);
INSERT INTO video_preview_clips_new (
id, library_id, rel_path, status, duration_seconds, file_size_bytes,
error_message, created_at, updated_at
)
SELECT
id, 1, file_path, status, duration_seconds, file_size_bytes,
error_message, created_at, updated_at
FROM video_preview_clips;
DROP TABLE video_preview_clips;
ALTER TABLE video_preview_clips_new RENAME TO video_preview_clips;
CREATE INDEX idx_preview_clips_rel_path ON video_preview_clips(rel_path);
CREATE INDEX idx_preview_clips_status ON video_preview_clips(status);
-- ---------------------------------------------------------------------------
-- 6. favorites: path → rel_path. Library-agnostic (cross-library sharing).
-- ---------------------------------------------------------------------------
ALTER TABLE favorites RENAME COLUMN path TO rel_path;
DROP INDEX IF EXISTS idx_favorites_path;
DROP INDEX IF EXISTS idx_favorites_unique;
CREATE INDEX idx_favorites_rel_path ON favorites(rel_path);
CREATE UNIQUE INDEX idx_favorites_unique ON favorites(userid, rel_path);
-- ---------------------------------------------------------------------------
-- 7. tagged_photo: photo_name → rel_path. Library-agnostic.
-- Dedup first so the (rel_path, tag_id) unique index can be created safely.
-- ---------------------------------------------------------------------------
ALTER TABLE tagged_photo RENAME COLUMN photo_name TO rel_path;
DELETE FROM tagged_photo
WHERE id NOT IN (
SELECT MIN(id) FROM tagged_photo GROUP BY rel_path, tag_id
);
DROP INDEX IF EXISTS idx_tagged_photo_photo_name;
DROP INDEX IF EXISTS idx_tagged_photo_count;
CREATE INDEX idx_tagged_photo_rel_path ON tagged_photo(rel_path);
CREATE UNIQUE INDEX idx_tagged_photo_relpath_tag ON tagged_photo(rel_path, tag_id);
PRAGMA foreign_keys=ON;
ANALYZE;

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@@ -0,0 +1,4 @@
-- No-op: there's no sensible way to recover which rows originally used
-- backslashes, and there's no reason to want backslashes back. The
-- deleted duplicates are also gone.
SELECT 1;

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@@ -0,0 +1,85 @@
-- Normalize `rel_path` columns to forward slashes. Windows ingest
-- historically produced a mix of `\` and `/`, which broke lookups and
-- caused spurious UNIQUE-constraint violations on re-registration.
--
-- SQLite enforces UNIQUE per-row during UPDATE, so we have to drop
-- losing duplicates BEFORE normalizing. For each table that has a
-- UNIQUE on rel_path, we delete rows whose normalized form already
-- exists in canonical (forward-slash) form — keeping the existing
-- forward-slash row as the survivor. Then a flat UPDATE finishes the
-- job for remaining backslash rows.
-- image_exif: UNIQUE(library_id, rel_path)
DELETE FROM image_exif
WHERE rel_path LIKE '%\%'
AND EXISTS (
SELECT 1 FROM image_exif AS other
WHERE other.library_id = image_exif.library_id
AND other.rel_path = REPLACE(image_exif.rel_path, '\', '/')
AND other.id != image_exif.id
);
UPDATE image_exif
SET rel_path = REPLACE(rel_path, '\', '/')
WHERE rel_path LIKE '%\%';
-- favorites: UNIQUE(userid, rel_path)
DELETE FROM favorites
WHERE rel_path LIKE '%\%'
AND EXISTS (
SELECT 1 FROM favorites AS other
WHERE other.userid = favorites.userid
AND other.rel_path = REPLACE(favorites.rel_path, '\', '/')
AND other.id != favorites.id
);
UPDATE favorites
SET rel_path = REPLACE(rel_path, '\', '/')
WHERE rel_path LIKE '%\%';
-- tagged_photo: UNIQUE(rel_path, tag_id)
DELETE FROM tagged_photo
WHERE rel_path LIKE '%\%'
AND EXISTS (
SELECT 1 FROM tagged_photo AS other
WHERE other.tag_id = tagged_photo.tag_id
AND other.rel_path = REPLACE(tagged_photo.rel_path, '\', '/')
AND other.id != tagged_photo.id
);
UPDATE tagged_photo
SET rel_path = REPLACE(rel_path, '\', '/')
WHERE rel_path LIKE '%\%';
-- entity_photo_links: UNIQUE(entity_id, library_id, rel_path, role)
DELETE FROM entity_photo_links
WHERE rel_path LIKE '%\%'
AND EXISTS (
SELECT 1 FROM entity_photo_links AS other
WHERE other.entity_id = entity_photo_links.entity_id
AND other.library_id = entity_photo_links.library_id
AND other.role = entity_photo_links.role
AND other.rel_path = REPLACE(entity_photo_links.rel_path, '\', '/')
AND other.id != entity_photo_links.id
);
UPDATE entity_photo_links
SET rel_path = REPLACE(rel_path, '\', '/')
WHERE rel_path LIKE '%\%';
-- video_preview_clips: UNIQUE(library_id, rel_path)
DELETE FROM video_preview_clips
WHERE rel_path LIKE '%\%'
AND EXISTS (
SELECT 1 FROM video_preview_clips AS other
WHERE other.library_id = video_preview_clips.library_id
AND other.rel_path = REPLACE(video_preview_clips.rel_path, '\', '/')
AND other.id != video_preview_clips.id
);
UPDATE video_preview_clips
SET rel_path = REPLACE(rel_path, '\', '/')
WHERE rel_path LIKE '%\%';
-- photo_insights has no UNIQUE on rel_path (history table), so a plain
-- normalize is safe.
UPDATE photo_insights
SET rel_path = REPLACE(rel_path, '\', '/')
WHERE rel_path LIKE '%\%';
ANALYZE;

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@@ -0,0 +1,23 @@
-- SQLite can't DROP COLUMN cleanly on older versions; rebuild the table.
CREATE TABLE photo_insights_backup AS
SELECT id, library_id, rel_path, title, summary, generated_at, model_version,
is_current, training_messages, approved
FROM photo_insights;
DROP TABLE photo_insights;
CREATE TABLE photo_insights (
id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT,
library_id INTEGER NOT NULL REFERENCES libraries(id),
rel_path TEXT NOT NULL,
title TEXT NOT NULL,
summary TEXT NOT NULL,
generated_at BIGINT NOT NULL,
model_version TEXT NOT NULL,
is_current BOOLEAN NOT NULL DEFAULT TRUE,
training_messages TEXT,
approved BOOLEAN
);
INSERT INTO photo_insights
SELECT id, library_id, rel_path, title, summary, generated_at, model_version,
is_current, training_messages, approved
FROM photo_insights_backup;
DROP TABLE photo_insights_backup;

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@@ -0,0 +1 @@
ALTER TABLE photo_insights ADD COLUMN backend TEXT NOT NULL DEFAULT 'local';

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@@ -0,0 +1,24 @@
-- SQLite can't DROP COLUMN cleanly on older versions; rebuild the table.
CREATE TABLE photo_insights_backup AS
SELECT id, library_id, rel_path, title, summary, generated_at, model_version,
is_current, training_messages, approved, backend
FROM photo_insights;
DROP TABLE photo_insights;
CREATE TABLE photo_insights (
id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT,
library_id INTEGER NOT NULL REFERENCES libraries(id),
rel_path TEXT NOT NULL,
title TEXT NOT NULL,
summary TEXT NOT NULL,
generated_at BIGINT NOT NULL,
model_version TEXT NOT NULL,
is_current BOOLEAN NOT NULL DEFAULT TRUE,
training_messages TEXT,
approved BOOLEAN,
backend TEXT NOT NULL DEFAULT 'local'
);
INSERT INTO photo_insights
SELECT id, library_id, rel_path, title, summary, generated_at, model_version,
is_current, training_messages, approved, backend
FROM photo_insights_backup;
DROP TABLE photo_insights_backup;

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@@ -0,0 +1 @@
ALTER TABLE photo_insights ADD COLUMN fewshot_source_ids TEXT;

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@@ -0,0 +1,2 @@
DROP TABLE IF EXISTS face_detections;
DROP TABLE IF EXISTS persons;

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-- Local face recognition tables.
--
-- `persons` are visual identities (the "who" of a face). The optional
-- `entity_id` bridges to the existing knowledge graph `entities` table —
-- when set, this person is the visual side of an LLM-extracted entity.
-- Don't auto-create entities from persons; the entity table represents
-- LLM-extracted knowledge with its own confidence semantics, and silently
-- filling it from face detections muddies the provenance.
--
-- `face_detections` carries one row per detected face on a content_hash,
-- plus marker rows with `status='no_faces'` or `status='failed'` so the
-- file watcher knows not to re-scan a hash. Keying on `content_hash`
-- (cross-library dedup) rather than `(library_id, rel_path)` means the
-- same JPEG in two libraries is scanned once. The denormalized `rel_path`
-- carries the most-recently-seen path — useful for cluster-thumb URL
-- generation; canonical path lookup goes through image_exif.
CREATE TABLE persons (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
name TEXT NOT NULL,
cover_face_id INTEGER, -- backfilled when the first face binds
entity_id INTEGER, -- optional bridge to entities(id)
created_from_tag BOOLEAN NOT NULL DEFAULT 0,
notes TEXT,
created_at BIGINT NOT NULL,
updated_at BIGINT NOT NULL,
CONSTRAINT fk_persons_entity FOREIGN KEY (entity_id) REFERENCES entities(id) ON DELETE SET NULL,
UNIQUE(name COLLATE NOCASE)
);
CREATE INDEX idx_persons_entity ON persons(entity_id);
CREATE TABLE face_detections (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
library_id INTEGER NOT NULL,
content_hash TEXT NOT NULL, -- canonical key (cross-library dedup)
rel_path TEXT NOT NULL, -- denormalized; most recently seen
bbox_x REAL, -- normalized 0..1; NULL on marker rows
bbox_y REAL,
bbox_w REAL,
bbox_h REAL,
embedding BLOB, -- 512×f32 = 2048 bytes; NULL on marker rows
confidence REAL, -- detector score
source TEXT NOT NULL, -- 'auto' | 'manual'
person_id INTEGER,
status TEXT NOT NULL DEFAULT 'detected', -- 'detected' | 'no_faces' | 'failed'
model_version TEXT NOT NULL, -- e.g. 'buffalo_l'; embedding lineage
created_at BIGINT NOT NULL,
CONSTRAINT fk_fd_library FOREIGN KEY (library_id) REFERENCES libraries(id),
CONSTRAINT fk_fd_person FOREIGN KEY (person_id) REFERENCES persons(id) ON DELETE SET NULL,
-- Detected rows carry geometry + embedding; marker rows ('no_faces',
-- 'failed') carry neither. CHECK enforces the invariant so manual
-- inserts can't slip through with half a row.
CONSTRAINT chk_marker CHECK (
(status = 'detected' AND bbox_x IS NOT NULL AND embedding IS NOT NULL)
OR (status IN ('no_faces','failed') AND bbox_x IS NULL AND embedding IS NULL)
)
);
CREATE INDEX idx_face_detections_hash ON face_detections(content_hash);
CREATE INDEX idx_face_detections_lib_path ON face_detections(library_id, rel_path);
CREATE INDEX idx_face_detections_person ON face_detections(person_id);
CREATE INDEX idx_face_detections_status ON face_detections(status);
-- One marker row per (content_hash, status='no_faces') so the file watcher
-- doesn't double-mark when a hash is seen on multiple full-scan passes.
CREATE UNIQUE INDEX idx_face_detections_no_faces_unique
ON face_detections(content_hash) WHERE status = 'no_faces';

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DROP INDEX IF EXISTS idx_persons_is_ignored;
ALTER TABLE persons DROP COLUMN is_ignored;

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@@ -0,0 +1,20 @@
-- IGNORE / junk bucket for the face recognition feature.
--
-- An "Ignored" person is the destination for strangers, faces the user
-- doesn't want tagged, and false detections. It looks like any other
-- person row (so face_detections.person_id stays a clean foreign key)
-- but `is_ignored=1` flags it for special UI treatment:
-- - hidden from the persons list by default
-- - excluded from `find_persons_by_names_ci` so a tag-name match
-- can never auto-bind a real face to the ignore bucket
-- - cluster-suggest already filters by `person_id IS NULL`, so faces
-- bound to an ignored person are naturally excluded from future
-- re-clustering
--
-- Partial index because the WHERE-clause is small (typically 1 row),
-- and we only ever query for `is_ignored = 1` to find the bucket.
ALTER TABLE persons ADD COLUMN is_ignored BOOLEAN NOT NULL DEFAULT 0;
CREATE INDEX idx_persons_is_ignored
ON persons(is_ignored) WHERE is_ignored = 1;

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DROP INDEX IF EXISTS idx_tags_name_nocase;

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@@ -0,0 +1,28 @@
-- Tags only enforced uniqueness in application code (the add_tag handler
-- looks up by name before inserting). The schema itself accepted dupes,
-- so a divergent code path could land two tags with the same name. Now
-- that we expose a rename endpoint we want a hard guarantee: case-
-- insensitive UNIQUE on tags.name.
-- Pre-flight: collapse exact-name duplicates (case-insensitive) onto the
-- lowest-id row before adding the constraint, otherwise the index
-- creation fails on any DB that ever produced dupes. On a clean DB this
-- is a no-op.
UPDATE tagged_photo
SET tag_id = (
SELECT MIN(t2.id) FROM tags t2
WHERE LOWER(t2.name) = LOWER((SELECT name FROM tags WHERE id = tagged_photo.tag_id))
)
WHERE tag_id IN (
SELECT t.id FROM tags t
WHERE t.id <> (
SELECT MIN(t2.id) FROM tags t2 WHERE LOWER(t2.name) = LOWER(t.name)
)
);
DELETE FROM tags
WHERE id <> (
SELECT MIN(t2.id) FROM tags t2 WHERE LOWER(t2.name) = LOWER(tags.name)
);
CREATE UNIQUE INDEX idx_tags_name_nocase ON tags (name COLLATE NOCASE);

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@@ -0,0 +1,5 @@
DROP INDEX IF EXISTS idx_photo_insights_content_hash;
ALTER TABLE photo_insights DROP COLUMN content_hash;
DROP INDEX IF EXISTS idx_tagged_photo_content_hash;
ALTER TABLE tagged_photo DROP COLUMN content_hash;

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-- Phase B of the multi-library data-model rollout: add a nullable
-- `content_hash` column to derived/user-intent tables that should follow
-- the bytes rather than the path. Reads will prefer hash-key joins and
-- fall back to rel_path while the column is null. A separate
-- reconciliation pass collapses duplicates as the column populates.
--
-- See CLAUDE.md → "Multi-library data model" for the policy. The
-- reference implementation is `face_detections`, which has been
-- hash-keyed since it was introduced.
--
-- Tables in this migration:
-- * tagged_photo — user-intent (tags follow the bytes)
-- * photo_insights — intrinsic to bytes (LLM-generated description)
--
-- favorites is the natural third candidate but its DAO is barely used in
-- v1 and the row count is tiny; deferring lets this migration stay
-- focused on the high-volume tables that drive cross-library overhead.
-- ---------------------------------------------------------------------------
-- tagged_photo
-- ---------------------------------------------------------------------------
ALTER TABLE tagged_photo ADD COLUMN content_hash TEXT;
-- Backfill: for each tagged_photo row, find the content_hash for its
-- rel_path. tagged_photo doesn't carry a library_id, so a rel_path that
-- exists under multiple libraries with different content is genuinely
-- ambiguous — we take the first matching image_exif row. The
-- reconciliation pass at runtime cleans up any rows that resolve
-- differently once a hash is known per library.
UPDATE tagged_photo
SET content_hash = (
SELECT content_hash FROM image_exif
WHERE image_exif.rel_path = tagged_photo.rel_path
AND image_exif.content_hash IS NOT NULL
LIMIT 1
)
WHERE content_hash IS NULL;
-- Hash-key index. Partial (only non-null rows) to keep the index small
-- during the transitional window where most rows are still null.
CREATE INDEX idx_tagged_photo_content_hash
ON tagged_photo (content_hash)
WHERE content_hash IS NOT NULL;
-- ---------------------------------------------------------------------------
-- photo_insights
-- ---------------------------------------------------------------------------
ALTER TABLE photo_insights ADD COLUMN content_hash TEXT;
-- Backfill keyed on (library_id, rel_path) — photo_insights already
-- carries library_id, so the resolution is unambiguous.
UPDATE photo_insights
SET content_hash = (
SELECT content_hash FROM image_exif
WHERE image_exif.library_id = photo_insights.library_id
AND image_exif.rel_path = photo_insights.rel_path
AND image_exif.content_hash IS NOT NULL
LIMIT 1
)
WHERE content_hash IS NULL;
CREATE INDEX idx_photo_insights_content_hash
ON photo_insights (content_hash)
WHERE content_hash IS NOT NULL;

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-- Requires SQLite 3.35+ for ALTER TABLE DROP COLUMN.
ALTER TABLE libraries DROP COLUMN enabled;

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-- Operator-controlled kill switch for a library. When `enabled = 0` the
-- watcher tick skips that library entirely — before the availability
-- probe, before ingest, before any maintenance pass — and the orphan-GC
-- all-online check treats it as out-of-scope rather than as a blocker.
--
-- The intended workflow is staging a new mount: insert with enabled=0,
-- verify the row appears in /libraries with enabled=false, then UPDATE
-- to 1 to start ingest. Same toggle works as a maintenance kill switch
-- after the fact ("don't keep probing this NAS while I'm rebooting it").
--
-- Default 1 so every existing library stays running on upgrade — no
-- behavior change without an explicit flip.
ALTER TABLE libraries ADD COLUMN enabled BOOLEAN NOT NULL DEFAULT 1;

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-- Requires SQLite 3.35+ for ALTER TABLE DROP COLUMN.
ALTER TABLE libraries DROP COLUMN excluded_dirs;

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-- Per-library excluded directories.
--
-- The global EXCLUDED_DIRS env var is the right knob for excludes that
-- every library shares (Synology @eaDir, .thumbnails, etc.). It's a
-- poor fit for "exclude this subtree from THIS library only", which
-- the natural use case for is mounting a parent directory while
-- another library already covers a child subtree underneath.
--
-- This column is parsed comma-separated, same shape as the env var,
-- and the watcher / memories / thumbnail walks each apply
-- (env_globals library.excluded_dirs) when scanning the library.
-- NULL = no extra excludes; the global env var still applies.
ALTER TABLE libraries ADD COLUMN excluded_dirs TEXT;

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DROP INDEX IF EXISTS idx_image_exif_duplicate_of_hash;
DROP INDEX IF EXISTS idx_image_exif_dhash;
DROP INDEX IF EXISTS idx_image_exif_phash;
ALTER TABLE image_exif DROP COLUMN duplicate_decided_at;
ALTER TABLE image_exif DROP COLUMN duplicate_of_hash;
ALTER TABLE image_exif DROP COLUMN dhash_64;
ALTER TABLE image_exif DROP COLUMN phash_64;

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-- Adds perceptual-hash signals + soft-mark resolution state to image_exif so
-- the duplicates surface in Apollo can group near-duplicates (re-encoded,
-- resized, format-converted copies) and let the user demote losers without
-- touching the file on disk. Image-only for v1: phash_64/dhash_64 are NULL
-- on videos and on images that fail to decode. See Apollo CLAUDE.md →
-- Duplicate detection / Caching layer for the policy.
--
-- Soft-mark columns are media-type-agnostic — when video perceptual hashing
-- arrives, it lives in a separate hash-keyed companion table and reuses the
-- same duplicate_of_hash / duplicate_decided_at machinery.
-- pHash (DCT, 64-bit) packed as i64 for fast XOR + popcount Hamming.
ALTER TABLE image_exif ADD COLUMN phash_64 BIGINT;
-- dHash (gradient, 64-bit). Cheap, robust to compression/resize. Stored
-- alongside pHash so the query layer can fall back if either is null.
ALTER TABLE image_exif ADD COLUMN dhash_64 BIGINT;
-- When non-null, this row is a soft-marked duplicate of the row whose
-- content_hash matches. The duplicate file stays on disk; the default
-- /photos listing filters it out. /photos?include_duplicates=true opts
-- back in (the Apollo duplicates modal uses this).
ALTER TABLE image_exif ADD COLUMN duplicate_of_hash TEXT;
-- Unix seconds of the resolve. Distinguishes "never reviewed" from
-- "reviewed and resolved" for the Apollo include_resolved toggle.
ALTER TABLE image_exif ADD COLUMN duplicate_decided_at BIGINT;
-- Partial indexes — the columns are NULL for the vast majority of rows
-- during the transitional window and forever for videos / decode failures.
CREATE INDEX idx_image_exif_phash
ON image_exif (phash_64)
WHERE phash_64 IS NOT NULL;
CREATE INDEX idx_image_exif_dhash
ON image_exif (dhash_64)
WHERE dhash_64 IS NOT NULL;
CREATE INDEX idx_image_exif_duplicate_of_hash
ON image_exif (duplicate_of_hash)
WHERE duplicate_of_hash IS NOT NULL;

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@@ -0,0 +1,2 @@
DROP INDEX IF EXISTS idx_image_exif_date_backfill;
ALTER TABLE image_exif DROP COLUMN date_taken_source;

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@@ -0,0 +1,24 @@
-- Tracks where a row's `date_taken` was sourced so the canonical-date
-- waterfall (kamadak-exif → exiftool → filename → earliest_fs_time) is
-- visible to debugging and to the per-tick backfill drain that re-runs
-- weak sources once stronger ones become available (e.g. exiftool gets
-- installed on a deploy that didn't have it). See CLAUDE.md → Memories
-- canonical-date pipeline.
--
-- Values:
-- 'exif' — kamadak-exif read DateTime/DateTimeOriginal directly
-- 'exiftool' — exiftool fallback caught a video / MakerNote / QuickTime tag
-- 'filename' — extract_date_from_filename matched a known pattern
-- 'fs_time' — fell through to earliest_fs_time(metadata)
--
-- NULL when `date_taken` itself is NULL (no source resolved the date).
ALTER TABLE image_exif ADD COLUMN date_taken_source TEXT;
-- Partial index for the per-tick backfill drain: targets rows that need
-- re-resolution (no date yet, or only the weakest source resolved it).
-- Filename-sourced rows are intentionally excluded — the regex is
-- authoritative when it matches and re-running exiftool wouldn't change
-- the answer.
CREATE INDEX idx_image_exif_date_backfill
ON image_exif (library_id, id)
WHERE date_taken IS NULL OR date_taken_source = 'fs_time';

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@@ -0,0 +1,9 @@
-- Reverting this migration is a no-op: the labels we wrote in `up.sql`
-- are correct under any state of the schema (every dated row was indeed
-- exif-sourced before the resolver landed), and there's no signal that
-- distinguishes "labelled by this migration" from "labelled by the
-- ingest path post-resolver". Clearing them would break the drain's
-- eligibility filter again.
--
-- The companion migration `2026-05-06-000000_add_date_taken_source` is
-- the one to revert if you need to remove the column entirely.

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@@ -0,0 +1,20 @@
-- Backfill `date_taken_source` for rows that pre-date the canonical-date
-- pipeline. Before the resolver landed, `image_exif.date_taken` could
-- only be populated via `exif::extract_exif_from_path` (kamadak-exif)
-- on the file-watcher, upload, or GPS-write paths. The resolver column
-- migration added `date_taken_source` defaulting to NULL, so every
-- historical row with a date is currently unlabelled — and the
-- per-tick drain skips them because its eligibility predicate is
-- `date_taken IS NULL OR date_taken_source = 'fs_time'`.
--
-- Label them `'exif'` once and let the drain take over from here. Safe
-- because every code path that wrote `date_taken` prior to the
-- resolver was a kamadak-exif read — there was no other source.
--
-- Idempotent: re-running this migration on a DB that has already been
-- backfilled is a no-op (the WHERE clause matches nothing the second
-- time around).
UPDATE image_exif
SET date_taken_source = 'exif'
WHERE date_taken IS NOT NULL
AND date_taken_source IS NULL;

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@@ -0,0 +1,2 @@
ALTER TABLE image_exif DROP COLUMN original_date_taken_source;
ALTER TABLE image_exif DROP COLUMN original_date_taken;

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@@ -0,0 +1,15 @@
-- Manual date_taken override: when an operator overrides a row's date via
-- POST /image/exif/date, the prior `(date_taken, date_taken_source)` is
-- snapshotted into these columns and the live columns hold the new value
-- with `date_taken_source = 'manual'`. POST /image/exif/date/clear restores
-- the pair and nulls the originals.
--
-- The waterfall source-name set is now:
-- 'exif' | 'exiftool' | 'filename' | 'fs_time' | 'manual'
--
-- The `idx_image_exif_date_backfill` partial index already filters to
-- `date_taken IS NULL OR date_taken_source = 'fs_time'`, so 'manual' rows
-- are naturally excluded from the per-tick backfill drain — no index
-- change needed.
ALTER TABLE image_exif ADD COLUMN original_date_taken BIGINT;
ALTER TABLE image_exif ADD COLUMN original_date_taken_source TEXT;

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@@ -0,0 +1,43 @@
-- Drop the persona-scoping column on entity_facts via the table-rebuild
-- dance for SQLite-version portability (matches the pattern in
-- 2026-04-20-000000_add_backend_to_insights/down.sql).
DROP INDEX IF EXISTS idx_entity_facts_persona;
CREATE TABLE entity_facts_backup AS
SELECT id, subject_entity_id, predicate, object_entity_id, object_value,
source_photo, source_insight_id, confidence, status, created_at
FROM entity_facts;
DROP TABLE entity_facts;
CREATE TABLE entity_facts (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
subject_entity_id INTEGER NOT NULL,
predicate TEXT NOT NULL,
object_entity_id INTEGER,
object_value TEXT,
source_photo TEXT,
source_insight_id INTEGER,
confidence REAL NOT NULL DEFAULT 0.6,
status TEXT NOT NULL DEFAULT 'active',
created_at BIGINT NOT NULL,
CONSTRAINT fk_ef_subject FOREIGN KEY (subject_entity_id) REFERENCES entities(id) ON DELETE CASCADE,
CONSTRAINT fk_ef_object FOREIGN KEY (object_entity_id) REFERENCES entities(id) ON DELETE SET NULL,
CONSTRAINT fk_ef_insight FOREIGN KEY (source_insight_id) REFERENCES photo_insights(id) ON DELETE SET NULL,
CHECK (object_entity_id IS NOT NULL OR object_value IS NOT NULL)
);
INSERT INTO entity_facts
SELECT id, subject_entity_id, predicate, object_entity_id, object_value,
source_photo, source_insight_id, confidence, status, created_at
FROM entity_facts_backup;
DROP TABLE entity_facts_backup;
CREATE INDEX idx_entity_facts_subject ON entity_facts(subject_entity_id);
CREATE INDEX idx_entity_facts_predicate ON entity_facts(predicate);
CREATE INDEX idx_entity_facts_status ON entity_facts(status);
CREATE INDEX idx_entity_facts_source_photo ON entity_facts(source_photo);
DROP INDEX IF EXISTS idx_personas_user;
DROP TABLE IF EXISTS personas;

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@@ -0,0 +1,64 @@
-- Personas live server-side now (mobile previously stored them in
-- AsyncStorage only). Each user gets the three built-ins seeded; custom
-- personas land here too via POST /personas or POST /personas/migrate.
--
-- `entity_facts` gains a persona_id so each persona accumulates its own
-- voice over a shared entity graph (entities themselves stay unscoped).
-- Existing rows backfill to 'default' via the column DEFAULT — that
-- becomes the historical baseline. The `include_all_memories` flag on
-- personas lets any persona opt back into reading the full pool.
CREATE TABLE personas (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
user_id INTEGER NOT NULL,
persona_id TEXT NOT NULL,
name TEXT NOT NULL,
system_prompt TEXT NOT NULL,
is_built_in BOOLEAN NOT NULL DEFAULT FALSE,
include_all_memories BOOLEAN NOT NULL DEFAULT FALSE,
created_at BIGINT NOT NULL,
updated_at BIGINT NOT NULL,
UNIQUE(user_id, persona_id),
CONSTRAINT fk_personas_user FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
);
CREATE INDEX idx_personas_user ON personas(user_id);
-- Seed built-ins for every existing user. System prompts copied verbatim
-- from FileViewer-React/hooks/usePersonas.tsx so server and client agree
-- on the canonical voice for each built-in.
INSERT INTO personas (user_id, persona_id, name, system_prompt, is_built_in, created_at, updated_at)
SELECT
u.id,
'default',
'Default Assistant',
'You are my long-term memory assistant. Use only the information provided. Do not invent details. Respond in 36 sentences in third person, leading with the most concrete moment from the photo and the surrounding context. Plain prose, no headings.',
TRUE,
strftime('%s', 'now') * 1000,
strftime('%s', 'now') * 1000
FROM users u
UNION ALL
SELECT
u.id,
'journal',
'Personal Journal',
'You are a personal journal writer. Write in first person, present tense, with warmth and reflection — focusing on emotions and meaningful moments. Use only the information provided; do not invent details. Aim for 48 sentences in a single flowing paragraph, no headings.',
TRUE,
strftime('%s', 'now') * 1000,
strftime('%s', 'now') * 1000
FROM users u
UNION ALL
SELECT
u.id,
'factual',
'Factual Reporter',
'You are a factual memory recorder. Be precise, objective, and concise. Lead with the date and place, then list what / when / who in 24 short sentences. Use only the information provided; if a detail is unknown, say so rather than guessing.',
TRUE,
strftime('%s', 'now') * 1000,
strftime('%s', 'now') * 1000
FROM users u;
-- Persona scoping on facts only. Entities and entity_photo_links stay
-- shared (real-world referents and shared photo ↔ entity associations).
ALTER TABLE entity_facts ADD COLUMN persona_id TEXT NOT NULL DEFAULT 'default';
CREATE INDEX idx_entity_facts_persona ON entity_facts(persona_id);

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@@ -0,0 +1,47 @@
-- Reverse 2026-05-10-000000_entity_facts_persona_fk: drop the
-- composite FK and the user_id column via the same rebuild pattern.
DROP INDEX IF EXISTS idx_entity_facts_user_persona;
DROP INDEX IF EXISTS idx_entity_facts_persona;
DROP INDEX IF EXISTS idx_entity_facts_source_photo;
DROP INDEX IF EXISTS idx_entity_facts_status;
DROP INDEX IF EXISTS idx_entity_facts_predicate;
DROP INDEX IF EXISTS idx_entity_facts_subject;
ALTER TABLE entity_facts RENAME TO entity_facts_old;
CREATE TABLE entity_facts (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
subject_entity_id INTEGER NOT NULL,
predicate TEXT NOT NULL,
object_entity_id INTEGER,
object_value TEXT,
source_photo TEXT,
source_insight_id INTEGER,
confidence REAL NOT NULL DEFAULT 0.6,
status TEXT NOT NULL DEFAULT 'active',
created_at BIGINT NOT NULL,
persona_id TEXT NOT NULL DEFAULT 'default',
CONSTRAINT fk_ef_subject FOREIGN KEY (subject_entity_id) REFERENCES entities(id) ON DELETE CASCADE,
CONSTRAINT fk_ef_object FOREIGN KEY (object_entity_id) REFERENCES entities(id) ON DELETE SET NULL,
CONSTRAINT fk_ef_insight FOREIGN KEY (source_insight_id) REFERENCES photo_insights(id) ON DELETE SET NULL,
CHECK (object_entity_id IS NOT NULL OR object_value IS NOT NULL)
);
INSERT INTO entity_facts
(id, subject_entity_id, predicate, object_entity_id, object_value,
source_photo, source_insight_id, confidence, status, created_at,
persona_id)
SELECT
id, subject_entity_id, predicate, object_entity_id, object_value,
source_photo, source_insight_id, confidence, status, created_at,
persona_id
FROM entity_facts_old;
DROP TABLE entity_facts_old;
CREATE INDEX idx_entity_facts_subject ON entity_facts(subject_entity_id);
CREATE INDEX idx_entity_facts_predicate ON entity_facts(predicate);
CREATE INDEX idx_entity_facts_status ON entity_facts(status);
CREATE INDEX idx_entity_facts_source_photo ON entity_facts(source_photo);
CREATE INDEX idx_entity_facts_persona ON entity_facts(persona_id);

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@@ -0,0 +1,82 @@
-- Add a real foreign key from entity_facts to personas. Until now,
-- entity_facts.persona_id was a free-form string with no integrity
-- guarantee — deleting a persona orphaned its facts, which then sat
-- forever in the readable-only-via-PersonaFilter::All hive-mind view.
--
-- personas is keyed (user_id, persona_id) so the FK has to be
-- composite. That requires entity_facts to carry user_id too, which
-- has the side benefit of fixing multi-user fact leakage on the read
-- path (without it, two users with the same 'default' persona would
-- see each other's default-scoped facts).
--
-- SQLite can't ALTER TABLE to add an FK; the table-rebuild dance is
-- the only way. Pattern matches 2026-05-09's down.sql and the older
-- 2026-04-20-000000 migration.
DROP INDEX IF EXISTS idx_entity_facts_subject;
DROP INDEX IF EXISTS idx_entity_facts_predicate;
DROP INDEX IF EXISTS idx_entity_facts_status;
DROP INDEX IF EXISTS idx_entity_facts_source_photo;
DROP INDEX IF EXISTS idx_entity_facts_persona;
ALTER TABLE entity_facts RENAME TO entity_facts_old;
CREATE TABLE entity_facts (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
subject_entity_id INTEGER NOT NULL,
predicate TEXT NOT NULL,
object_entity_id INTEGER,
object_value TEXT,
source_photo TEXT,
source_insight_id INTEGER,
confidence REAL NOT NULL DEFAULT 0.6,
status TEXT NOT NULL DEFAULT 'active',
created_at BIGINT NOT NULL,
persona_id TEXT NOT NULL DEFAULT 'default',
user_id INTEGER NOT NULL DEFAULT 1,
CONSTRAINT fk_ef_subject FOREIGN KEY (subject_entity_id) REFERENCES entities(id) ON DELETE CASCADE,
CONSTRAINT fk_ef_object FOREIGN KEY (object_entity_id) REFERENCES entities(id) ON DELETE SET NULL,
CONSTRAINT fk_ef_insight FOREIGN KEY (source_insight_id) REFERENCES photo_insights(id) ON DELETE SET NULL,
CONSTRAINT fk_ef_persona FOREIGN KEY (user_id, persona_id) REFERENCES personas(user_id, persona_id) ON DELETE CASCADE,
CHECK (object_entity_id IS NOT NULL OR object_value IS NOT NULL)
);
-- Backfill: assign each legacy fact to the user that owns the matching
-- persona. Built-ins are seeded per-user with the same persona_id
-- string for everyone, so MIN(user_id) deterministically picks the
-- earliest registered user (typically user 1, the operator). Custom
-- persona_ids exist for at most one user, so MIN is also unique.
-- Falls back to user_id=1 when no matching persona row exists; in that
-- case the FK below would still fail, but legacy rows shouldn't be in
-- that state because 2026-05-09 ADD COLUMN defaulted persona_id to
-- 'default', which is seeded for every user.
INSERT INTO entity_facts
(id, subject_entity_id, predicate, object_entity_id, object_value,
source_photo, source_insight_id, confidence, status, created_at,
persona_id, user_id)
SELECT
old.id,
old.subject_entity_id,
old.predicate,
old.object_entity_id,
old.object_value,
old.source_photo,
old.source_insight_id,
old.confidence,
old.status,
old.created_at,
old.persona_id,
COALESCE(
(SELECT MIN(p.user_id) FROM personas p WHERE p.persona_id = old.persona_id),
1
)
FROM entity_facts_old old;
DROP TABLE entity_facts_old;
CREATE INDEX idx_entity_facts_subject ON entity_facts(subject_entity_id);
CREATE INDEX idx_entity_facts_predicate ON entity_facts(predicate);
CREATE INDEX idx_entity_facts_status ON entity_facts(status);
CREATE INDEX idx_entity_facts_source_photo ON entity_facts(source_photo);
CREATE INDEX idx_entity_facts_persona ON entity_facts(persona_id);
CREATE INDEX idx_entity_facts_user_persona ON entity_facts(user_id, persona_id);

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@@ -0,0 +1,5 @@
-- SQLite can drop columns since 3.35 (March 2021); embedded
-- libsqlite3-sys is well past that. Drop in reverse insert order so
-- a partial down still leaves the schema valid.
ALTER TABLE entity_facts DROP COLUMN valid_until;
ALTER TABLE entity_facts DROP COLUMN valid_from;

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@@ -0,0 +1,25 @@
-- Add valid-time columns to entity_facts.
--
-- entity_facts already has created_at — *transaction time*, the
-- moment WE recorded the fact. That's not the same as the real-world
-- period the fact was true. "Cameron is_in_relationship_with X" was
-- only true during a window; recording it in 2026 doesn't make it
-- true today. Without the distinction, every former relationship,
-- former job, former address reads as currently-true.
--
-- Adding two BIGINT NULL columns: valid_from / valid_until (unix
-- seconds). NULL means "unbounded on that side" — `valid_from IS
-- NULL` reads as "always-true-back-to-the-beginning",
-- `valid_until IS NULL` as "still-true-now-or-unknown". Both NULL =
-- temporal validity unknown (current state of all legacy rows).
--
-- Conflict detection refines accordingly: same-predicate facts with
-- different objects stop flagging when their intervals are disjoint
-- ("lives_in NYC 2018-2020" and "lives_in SF 2020-present" are both
-- valid, just at different times).
ALTER TABLE entity_facts ADD COLUMN valid_from BIGINT;
ALTER TABLE entity_facts ADD COLUMN valid_until BIGINT;
-- Optional partial index for time-bounded scans. Skipped for now —
-- conflict detection runs per-entity (small N) and doesn't need it.

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@@ -0,0 +1,2 @@
DROP INDEX IF EXISTS idx_entity_facts_superseded_by;
ALTER TABLE entity_facts DROP COLUMN superseded_by;

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@@ -0,0 +1,31 @@
-- Add a supersession pointer to entity_facts.
--
-- Status alone is a one-way trapdoor: 'rejected' loses the link
-- between the rejected fact and the one that replaced it. For
-- evolving facts (Cameron's relationship, employer, address) the
-- curator wants to *replace* a stale fact with a new one and keep
-- the history readable: "from 2018 until 2022 this was true, then
-- it became this other thing".
--
-- A nullable INTEGER column pointing at another entity_facts.id —
-- no FK constraint because SQLite can't ALTER ADD COLUMN with REFs;
-- the DAO's delete_fact clears dangling pointers in the same
-- transaction as the parent delete to keep the column honest.
--
-- A status of 'superseded' on the old fact (alongside the existing
-- active / reviewed / rejected) signals "replaced by a newer
-- claim". Read paths already filter 'rejected' out of the active
-- view; the curation UI will treat 'superseded' the same way for
-- conflict detection so they don't keep flagging.
--
-- Pairs with the valid-time columns from 2026-05-10-000100: the
-- supersede action auto-stamps the old fact's `valid_until` from
-- the new fact's `valid_from`, closing the interval cleanly.
ALTER TABLE entity_facts ADD COLUMN superseded_by INTEGER;
-- Helpful index for "show me what superseded this fact" walks
-- (rare today; cheap to add now while the table is small).
CREATE INDEX idx_entity_facts_superseded_by
ON entity_facts(superseded_by)
WHERE superseded_by IS NOT NULL;

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@@ -0,0 +1,4 @@
DROP INDEX IF EXISTS idx_entity_facts_created_by_backend;
DROP INDEX IF EXISTS idx_entity_facts_created_by_model;
ALTER TABLE entity_facts DROP COLUMN created_by_backend;
ALTER TABLE entity_facts DROP COLUMN created_by_model;

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@@ -0,0 +1,30 @@
-- Track which model + backend generated each fact so the curator
-- can audit which configurations produce trustworthy knowledge.
--
-- photo_insights already carries `model_version` + `backend`, and
-- entity_facts.source_insight_id links to it — but:
-- 1. source_insight_id is only set after an insight is stored
-- (post-loop), so chat-continuation facts and facts whose insight
-- was regenerated lose the link.
-- 2. JOINing for every read is more friction than just embedding the
-- provenance on the fact row itself.
-- 3. Manual facts (POST /knowledge/facts) have no insight at all and
-- need to record "manual" as their provenance.
--
-- Two nullable TEXT columns are enough for the audit use case: model
-- (e.g. "qwen2.5:7b", "anthropic/claude-sonnet-4") and backend
-- ("local", "hybrid", "manual"). Pre-existing rows leave both NULL —
-- legacy facts predate this tracking and can't be back-filled
-- reliably from training_messages without burning compute.
ALTER TABLE entity_facts ADD COLUMN created_by_model TEXT;
ALTER TABLE entity_facts ADD COLUMN created_by_backend TEXT;
-- Indexes are cheap and useful for "show me all facts from model X"
-- audit queries — partial so the legacy NULL rows don't bloat them.
CREATE INDEX idx_entity_facts_created_by_model
ON entity_facts(created_by_model)
WHERE created_by_model IS NOT NULL;
CREATE INDEX idx_entity_facts_created_by_backend
ON entity_facts(created_by_backend)
WHERE created_by_backend IS NOT NULL;

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@@ -0,0 +1 @@
ALTER TABLE personas DROP COLUMN reviewed_only_facts;

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@@ -0,0 +1,16 @@
-- Per-persona toggle: when true, agent reads only see facts whose
-- status is exactly 'reviewed' (human-verified). When false (the
-- default), agent reads see 'active' OR 'reviewed' — everything not
-- rejected or superseded.
--
-- The mobile app surfaces this as "Strict mode" on the persona
-- editor: useful when you want a persona's chat to be grounded
-- exclusively on the curated subset, e.g. for tasks where
-- hallucinated agent claims are particularly costly.
--
-- Note: this is separate from `include_all_memories` (which unions
-- across personas for hive-mind reads). Reviewed-only operates on
-- the status axis; include_all_memories operates on the persona-
-- scope axis. They compose freely.
ALTER TABLE personas ADD COLUMN reviewed_only_facts BOOLEAN NOT NULL DEFAULT 0;

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