Commit Graph

3 Commits

Author SHA1 Message Date
Taylor Eernisse
65583ed5d6 refactor: Remove redundant doc comments throughout codebase
Removes module-level doc comments (//! lines) and excessive inline doc
comments that were duplicating information already evident from:
- Function/struct names (self-documenting code)
- Type signatures (the what is clear from types)
- Implementation context (the how is clear from code)

Affected modules:
- cli/* - Removed command descriptions duplicating clap help text
- core/* - Removed module headers and obvious function docs
- documents/* - Removed extractor/regenerator/truncation docs
- embedding/* - Removed pipeline and chunking docs
- gitlab/* - Removed client and transformer docs (kept type definitions)
- ingestion/* - Removed orchestrator and ingestion docs
- search/* - Removed FTS and vector search docs

Philosophy: Code should be self-documenting. Comments should explain
"why" (business decisions, non-obvious constraints) not "what" (which
the code itself shows). This change reduces noise and maintenance burden
while keeping the codebase just as understandable.

Retains comments for:
- Non-obvious business logic
- Important safety invariants
- Complex algorithm explanations
- Public API boundaries where generated docs matter

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-05 00:04:32 -05:00
Taylor Eernisse
7d07f95d4c fix(embedding): Harden pipeline against chunk overflow, config drift, and partial failures
Reduces CHUNK_MAX_BYTES from 32KB to 6KB and CHUNK_OVERLAP_CHARS from
500 to 200 to stay within nomic-embed-text's 8,192-token context
window. This commit addresses all downstream consequences of that
reduction:

- Config drift detection: find_pending_documents and
  count_pending_documents now take model_name and compare
  chunk_max_bytes, model, and dims against stored metadata. Documents
  embedded with stale config are automatically re-queued.

- Overflow guard: documents producing >= CHUNK_ROWID_MULTIPLIER chunks
  are skipped with a sentinel error recorded in embedding_metadata,
  preventing both rowid collision and infinite re-processing loops.

- Deferred clearing: old embeddings are no longer cleared before
  attempting new ones. clear_document_embeddings is deferred until the
  first successful chunk embedding, so if all chunks fail the document
  retains its previous embeddings rather than losing all data.

- Savepoints: each page of DB writes is wrapped in a SQLite savepoint
  so a crash mid-page rolls back atomically instead of leaving partial
  state (cleared embeddings with no replacements).

- Per-chunk retry on context overflow: when a batch fails with a
  context-length error, each chunk is retried individually so one
  oversized chunk doesn't poison the entire batch.

- Adaptive dedup in vector search: replaces the static 3x over-fetch
  multiplier with a dynamic one based on actual max chunks per document
  (using the new chunk_count column with a fallback COUNT query for
  pre-migration data). Also replaces partial_cmp with total_cmp for
  f64 distance sorting.

- Stores chunk_max_bytes and chunk_count (on sentinel rows) in
  embedding_metadata to support config drift detection and adaptive
  dedup without runtime queries.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 09:35:08 -05:00
Taylor Eernisse
723703bed9 feat(embedding): Add Ollama-powered vector embedding pipeline
Implements the embedding module that generates vector representations
of documents using a local Ollama instance with the nomic-embed-text
model. These embeddings enable semantic (vector) search and the hybrid
search mode that fuses lexical and semantic results via RRF.

Key components:

- embedding::ollama: HTTP client for the Ollama /api/embeddings
  endpoint. Handles connection errors with actionable error messages
  (OllamaUnavailable, OllamaModelNotFound) and validates response
  dimensions.

- embedding::chunking: Splits long documents into overlapping
  paragraph-aware chunks for embedding. Uses a configurable max token
  estimate (8192 default for nomic-embed-text) with 10% overlap to
  preserve cross-chunk context.

- embedding::chunk_ids: Encodes chunk identity as
  doc_id * 1000 + chunk_index for the embeddings table rowid. This
  allows vector search to map results back to documents and
  deduplicate by doc_id efficiently.

- embedding::change_detector: Compares document content_hash against
  stored embedding hashes to skip re-embedding unchanged documents,
  making incremental embedding runs fast.

- embedding::pipeline: Orchestrates the full embedding flow: detect
  changed documents, chunk them, call Ollama in configurable
  concurrency (default 4), store results. Supports --retry-failed
  to re-attempt previously failed embeddings.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-30 15:46:30 -05:00