Trialing Qwen3-Embedding-0.6B (1024-dim, instruct-prefixed queries)
against nomic required code changes at every hardcoded seam; now it's a
config flip plus a reembed_embeddings run.
- EMBEDDING_DIM env (default 768) replaces every hardcoded dim check:
daily summary / calendar / search / location DAOs, Ollama batch
validation, reembed_embeddings
- entities gains the dim guard it never had — a wrong-dim vector
silently kills dedup/recall (cosine over mismatched lengths is 0),
so store None and warn instead
- embed_query / embed_document split with EMBED_QUERY_PREFIX /
EMBED_DOCUMENT_PREFIX (literal \n expanded): retrieval models treat
the two sides differently — nomic wants search_query:/search_document:,
Qwen3 wants Instruct:...\nQuery: on queries only. All query-side
call sites and all corpus writers now declare their side.
- document the contract in CLAUDE.md: change the model or any of these
vars → re-run reembed_embeddings or search is garbage
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Every map_err(|_| DbError::new(...)) and map_err(|_| anyhow!("..."))
in the database layer was discarding the actual Diesel/SQLite error,
making failures impossible to diagnose from logs.
- Add DbError::log() that logs the source error before converting
- Replace all ~130 swallowed outer map_err closures with DbError::log
- Replace all ~47 swallowed inner anyhow closures to include the
source error in the message
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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>
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>
Cameron Cordes
Cameron