Changelog

ratel-ai-core release history · crates.io · source · docs.rs

Synced verbatim from the package's CHANGELOG.md at ratel-ai/ratel@3be0ecb — do not edit by hand. Regenerate with pnpm sync:api in apps/docs.

All notable changes to ratel-ai-core are documented here.

The format follows Keep a Changelog and this crate adheres to Semantic Versioning.

[0.4.0] - 2026-07-09

Fixed

• Re-registering a tool or skill (MCP re-sync, hot-reload) left a stale duplicate in the corpus instead of replacing it in place, causing BM25 score drift and an unbounded memory leak. ToolRegistry/SkillRegistry are now id-keyed so register replaces in place, and the dense embedding cache invalidates on replace so build_embeddings re-embeds the changed id.

[0.3.0] - 2026-07-06

Added

• Selectable retrieval methods (ADR-0011): a SearchMethod enum — Bm25 (default), Semantic, Hybrid — chosen per registry or per call via ToolRegistry::search_with_method / SkillRegistry::search_with_method. Semantic ranks a local BAAI/bge-small-en-v1.5 embedding (pure-Rust Candle); hybrid fuses the BM25 and dense arms with Reciprocal Rank Fusion (no reranker).
• EmbedderError (surfaced from search_with_method on the semantic/hybrid path) and a TraceEvent::EmbedderLoad / EmbedderLoadStatus flagging a slow (possibly underpowered machine) or failed model load.
• ToolRegistry::build_embeddings / SkillRegistry::build_embeddings — pre-compute embeddings for not-yet-embedded tools/skills so a later semantic/hybrid search only embeds the query.

Changed

• BM25 remains the default engine. search / search_with_origin keep their infallible Vec<SearchHit> signature and BM25 behavior unchanged.
• The dense embedding cache is now incremental — a growing prefix of the corpus. register only appends (never invalidates), and build_embeddings embeds only newly-registered tools, so an existing vector is never recomputed (adding one tool costs one embedding, not N). A BM25-only registry still never loads the model.
• A semantic/hybrid search over an un-built corpus now returns EmbedderError::EmbeddingsNotBuilt instead of embedding inside the search path — a search never silently pays the corpus-embedding cost. Populate the cache with build_embeddings() first.

[0.2.1-rc.1] - 2026-07-04

Changed

• First release cut under the per-package release scheme (ADR-0008): ratel-ai-core now versions and ships independently, tagged core-v*. No crate API changes since 0.2.0.

[0.2.0] - 2026-06-16

Added

• First-class skills: a Skill { id, name, description, tags, tools, metadata, body } type and a separate SkillRegistry BM25 index — ranked independently of tools. Only name/description/tags are indexed; tools (a declared dependency edge surfaced at the gateway), metadata (non-indexed context such as stacks), and body are not. Plus skill_search / skill_churn / skill_invoke trace events for the retrieval funnel.

[0.1.6] - 2026-06-10

Changed

• Version bump for the coordinated v0.1.6 release (first release shipping the ratel-ai Python SDK). No crate source changes since 0.1.5; re-published in lockstep to keep all artifacts version-aligned.

[0.1.5] - 2026-05-10

Added

• Initial release on the v1 (revamp) line. BM25 tool retrieval, MCP ingestion, framework-neutral catalog. See the crate README for the full surface.
• trace module: TraceEvent tagged enum, TraceEnvelope, TraceSink trait with NoopSink, MemorySink, and JsonlSink (synchronous O_APPEND, mode 0600 on Unix) — single tagged event stream per ADR-0007. ToolRegistry::with_trace_sink / set_trace_sink / record_event plus a search_with_origin method. register emits index_churn{Add}; search emits search with a bm25 stage. The origin enum tags each search as direct (Rust callers, pre-fetch helpers, benchmarks) or agent (LLM-synthesized via the gateway), to let downstream consumers separate the two paths.