Onboarding now asks the user once, on first run, whether to use the
multilingual embedding model. The default answer is yes — defaulting to
English-only made the recall promise effectively unreachable for any
non-English content (cross-lingual cos ~0.35 vs ~0.88 for the multilingual
model). The choice is written to config.json so subsequent runs pick the
right EF without re-prompting; existing installs that never set the env
var or ran onboarding stay on minilm for back-compat. MEMPALACE_EMBEDDING_MODEL
still overrides both.
Multilingual deps (huggingface_hub, tokenizers, numpy) move from the
[multilingual] extra into core. The extra is kept as a no-op alias so
existing install scripts keep working. The 300 MB ONNX model is still
lazy-downloaded on first use, not at install time.
`quick_setup` (the programmatic non-interactive path) grows an optional
`embedding_model` arg so tests and benchmark scripts can pick a model
without writing config.json by accident.
EmbeddinggemmaONNX's "missing deps" error now points at the right
recovery path (reinstall mempalace, since the deps are core) rather
than the obsolete pip install mempalace[multilingual] hint.
Tests: 9 new (3 _ask_embedding_model variants + 2 run_onboarding
persistence + 2 quick_setup + 2 set_embedding_model round-trips). The
existing 2 run_onboarding tests now patch _ask_embedding_model so they
don't print to stdout.
On Windows with non-UTF-8 locale (e.g. GBK), Path.read_text() defaults
to platform encoding, breaking onboarding tests and any source code that
reads JSON/markdown with non-ASCII content.
5 files, 8 call sites fixed.
- Add tests for config, convo_miner, spellcheck, knowledge_graph
- Fix Windows PermissionError in test cleanup (chromadb file locks)
- Add UTF-8 encoding to split_mega_files, entity_registry, hooks_cli
- Fix mcp_server parse_known_args logging for unknown args
- Set coverage threshold to 85 in pyproject.toml and CI
- Reset all version files to 3.0.11
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Igor Lins e Silva