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>
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>
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>
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>
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>
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>
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>
