Aquesta és una versió anterior. La versió actual és la 1.3.0. ivygrep 1.3.0 · Data de publicació:
Fitxers d’instal·lació 1.2.12
| Arquitectura | Tipus | Àmbit | Mida del fitxer | Baixa | SHA256 |
|---|---|---|---|---|---|
| 64 bits | ZIP → Portable | — | — | github.com | VirusTotal |
L’enllaç i l’SHA256 provenen del manifest comunitari del Gestor de paquets del Windows. Convé comparar el hash del fitxer baixat abans d’executar-lo.
Notes de la versió
### Security
• Upgraded the Hugging Face HTTP dependency chain to eliminate `RUSTSEC-2026-0258` from the inherited `h2` dependency.
### Fixed
• CLI search, task context, and MCP now preserve brace-alternative globs, mixed path filters, character classes, and escaped commas.
• Semantic filtering retains include-glob alternatives and filename-based language overrides without incorrectly narrowing complex patterns.
• Linked Git worktrees complete background neural enhancement and safely share base-index search leases.
• Neural query caches invalidate when model identity changes, watcher failures are retried, regex candidate coverage is complete, and index storage stays excluded from indexed workspaces.
### Performance
• Reuse embeddings when unchanged source chunks shift and keep AST chunk generation bounded.
• Seek directory-scoped and selective glob searches through indexed SQLite ranges instead of scanning candidate paths.
• Retain hot query, neural, readiness, workspace, and search-context entries with bounded LRU caches.
• Adapt Tantivy writer parallelism and memory to changed source size, reducing measured fresh-index latency by 22% at 30,001 chunks and 33% at 100,001 chunks.
• Speed up all-workspace discovery and avoid redundant generated-corpus benchmark compilation.
### Testing
• Required CI now enforces lexical/hash and verified neural retrieval relevance, including nDCG, MRR, candidate recall, and zero-hit thresholds.
• Fresh-index profiling reports individual SQLite, Tantivy, vector-counting, merge, and publication phases.
• CI workflows cancel superseded pull-request runs and distinguish every platform/backend matrix job.
