Automated formatting and lint corrections from parallel agent work:
- cargo fmt: import reordering (alphabetical), line wrapping to respect
max width, trailing comma normalization, destructuring alignment,
function signature reformatting, match arm formatting
- clippy (pedantic): Range::contains() instead of manual comparisons,
i64::from() instead of `as i64` casts, .clamp() instead of
.max().min() chains, let-chain refactors (if-let with &&),
#[allow(clippy::too_many_arguments)] and
#[allow(clippy::field_reassign_with_default)] where warranted
- Removed trailing blank lines and extra whitespace
No behavioral changes. All existing tests pass unmodified.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements the search module providing three search modes:
- Lexical (FTS5): Full-text search using SQLite FTS5 with safe query
sanitization. User queries are automatically tokenized and wrapped
in proper FTS5 syntax. Supports a "raw" mode for power users who
want direct FTS5 query syntax (NEAR, column filters, etc.).
- Semantic (vector): Embeds the search query via Ollama, then performs
cosine similarity search against stored document embeddings. Results
are deduplicated by doc_id since documents may have multiple chunks.
- Hybrid (default): Executes both lexical and semantic searches in
parallel, then fuses results using Reciprocal Rank Fusion (RRF) with
k=60. This avoids the complexity of score normalization while
producing high-quality merged rankings. Gracefully degrades to
lexical-only when embeddings are unavailable.
Additional components:
- search::filters: Post-retrieval filtering by source_type, author,
project, labels (AND logic), file path prefix, created_after, and
updated_after. Date filters accept relative formats (7d, 2w) and
ISO dates.
- search::rrf: Reciprocal Rank Fusion implementation with configurable
k parameter and optional explain mode that annotates each result
with its component ranks and fusion score breakdown.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
