--- title: "Changelog" url: https://recursiveai.org/oneindex/docs/changelog/ description: "All notable changes are listed here. The format follows Keep a Changelog and the project follows Semantic Versioning." version: "0.4.0-preview.2" source: https://github.com/recursive-ai-oss/oneindex-csharp/blob/177f49bb3974e9e44df6d1a800342a9d353a0984/CHANGELOG.md --- # Changelog All notable changes are listed here. The format follows [Keep a Changelog](https://keepachangelog.com/en/1.1.0/) and the project follows [Semantic Versioning](https://semver.org/). ## [Unreleased] ## [0.4.0-preview.2] - 2026-11-03 - **Fixed: Entity Framework Core inline apply skipped the first `SaveChanges`.** With `ApplyInline = true` and no `ContextFactory` (the configuration of the documented sample), the runtime had not yet learned how to create its own context when the first `SaveChanges` finished, so that save was not applied to the index. The error was kept only in `OneIndexRuntime.LastApplyError` and searches returned nothing for it. The rows were safely in the outbox. Anyone using `RecursiveAI.OneIndex.EntityFrameworkCore` 0.4.0-preview.1 that way should upgrade; after the upgrade the first apply (the next `SaveChanges`, or `OneIndexRuntime.For(db).CatchUp()`) catches the index up from the outbox, so nothing needs re-entering. On 0.4.0-preview.1 itself, calling `OneIndexRuntime.For(db)` once (any search through the context does) and then `CatchUp()` or `ReindexAsync` does the same. The context is now learned before the first change is saved. A configuration that can never apply (no `ContextFactory` and no public constructor taking the context's `DbContextOptions`) now throws `InvalidOperationException` from `SaveChanges` (with `ApplyInline`) or `RunAsync`, before anything is written, instead of failing silently. - The `oneindex` tool's `--version` prints the package version (for example `0.4.0-preview.2`), not the four-number assembly version. - Documentation: the install line for the tool needs `--prerelease`; package sizes (`.Models` 134 MB, `.Models.Multilingual` 112 MB, the tool 151 MB); the README says the previews are on nuget.org; the EF and `.Files` kill-campaign figures and the static index's first-query bytes (about 0.65 MB for the query, 0.74 MB with the manifest) agree across documents; internal markers removed from the synonyms and did-you-mean pages; the benchmark method page says where the published rows are. ## [0.4.0-preview.1] - 2026-11-03 The first public preview. - Static index: term dictionaries and lengths are read in 4 KiB pages on first use and scattered files use 4 KiB chunks (`StaticBuildOptions.ScatteredChunkBytes`, `oneindex static build --scattered-kb`), so a first query fetches about 0.63 MB instead of 2.6 MB. Static hybrid search takes its vector arm from IVF (`StaticIndex.HybridNprobe`). - IVF as a per-field vector index on the server (`[Vector(Index = VectorIndexKind.Ivf, IvfLists = n)]`), stored in a new segment part `ivf`. - Query JSON: a ranking rule naming a field that cannot be sorted is a positioned parse error instead of an exception. - Multi-vector auto-encoding: `[MultiVector(From = ...)]` encodes the source text at upsert through an `IMultiVectorEncoder` (`SearchIndex.Open(path, embedder, sparse, reranker, multiVectorEncoder)` or `SearchMultiVectorEncoders.Default`), caches by model identity and text in stored source, re-encodes stale entries in `ReembedStale()`, and `SearchQuery.MaxSim(...)` is the late-interaction query stage beside `Rerank`. `IMultiVectorEncoder` gains batch `Encode`/`EncodeAsync` with default implementations. - Windows: file handles allow sharing delete, rename replaces a destination that a reader has open, and readers use ordinary handles so cached lookups allocate nothing; the full test suite now runs on Windows in CI. The browser smoke app builds on its own CI job (it needs the wasm-tools workload) instead of with the solution. - Durability harness: the campaigns start their child processes correctly whether run through `dotnet run`, `dotnet Durability.dll` or the application host. - `RecursiveAI.OneIndex.Analysis.Asian`: Japanese and Korean lattice segmentation (IPADIC, mecab-ko-dic), Chinese most-probable-path segmentation (jieba word list) and Thai, Lao, Khmer and Myanmar maximal matching (ICU word lists), as the analyzers `ja`, `ko`, `zh`, `th`, `lo`, `km` and `my` (`AsianAnalyzers.Register()`; core gains `AnalyzerRegistry.Register`). Dictionaries are a checksummed container format (`OIDICT` 1) with typed errors. - Decompounding in core: `CompoundSplitter` (Koehn and Knight splitting, fewest parts first), `DecompoundFilter`, packed word lists for de, nl, sv, da, no, fi and is, and the analyzers `-compound` and `-compound-both`. - `RecursiveAI.OneIndex.Models`: SentencePiece unigram tokenizer (`SentencePieceModel`, `SentencePieceTokenizer`) with the nmt_nfkc normalizer. - New package `RecursiveAI.OneIndex.Models.Multilingual`: `MultilingualE5Embedder` (multilingual-e5-small, int8 weights packed). - More-like-this: `MoreLikeThisQuery` picks the most distinctive terms of a text or a stored document by term frequency times idf and searches them; `index.MoreLikeThis(id)`, `index.MoreLikeThisText(text)` and the query JSON node `moreLikeThis` (docs/more-like-this.md). A missing source document raises `SourceDocumentNotFoundException`. - Facet value search on the happy path: `search.FacetValues(x => x.Category, "sho")` counts over the documents of that search. - Release builds fetch the packed model weights from a release asset checked against a pinned SHA-256 and fail without them (`tools/models/fetch-release-weights.sh`). ## [0.3.0-preview.1] - 2026-11-03 - Commit format 3: a flushed segment writes its text, column, point, stored and identifier parts into one pack file, so a small commit adds two files instead of eight (fewer flushes to disk per commit). Indexes written by earlier formats open, search and merge unchanged. - Term proximity: user-text searches add a proximity bonus to the BM25F score (after Büttcher, Clarke and Lushman, SIGIR 2006), weight 0.1 by default; typed queries are unchanged. - Ranking rules (opt-in): a bucket-sort order of `words`, `typo`, `proximity`, `attribute`, `sort` and `exactness` rules, declared with `[RankingRules(...)]`, set per search with `.RankingRules(...)`, or given as `rankingRules` in query JSON. - Query JSON: a string holding an unpaired surrogate escape is a positioned parse error instead of an exception. - Term dictionary format 2: nodes keep their labels, cumulative term counts and child distances in fixed-width tables, so an arc is found by label and fuzzy, typo and as-you-type expansion can look up only the arcs a Levenshtein state can still use. Fuzzy automata share precomputed shape transitions across queries. Version 1 segments stay readable and are rewritten as version 2 when merged. - Block-max WAND re-sorts its clauses from the previous round's order instead of from scratch, which makes disjunctions of dozens of terms (fuzzy and typo expansions) about twice as fast. - Merge policy: `TieredMergePolicy.SizeRatio` (default 2) also merges the smallest segments when the largest of a group is at most that many times the others combined, so a settled index keeps a handful of segments and fuzzy, typo and prefix queries walk fewer term dictionaries; set it to 0 for the plain tiered policy. Bulk loads rewrite documents more often (about 3.8 times at 15 flushes against 1.7). - Filtered nearest-neighbour search: a filter now steers the HNSW walk (only passing documents are scored, with neighbours-of-neighbours expansion through rejected nodes, after the ACORN paper) and a selective filter switches to an exact scan of the passing vectors; both work on the compressed copies. ## [0.1.0-preview.1] - 2026-11-01 - Automatic embedding: `[Vector(From = ...)]` embeds the source text at upsert through the index's embedder (`SearchIndex.Open(path, embedder)` or `SearchEmbedders.Default`; `BgeSmallEmbedder.UseAsDefault()` in the models package), keeps the text and model identity digest beside the vector in stored source so reindexing, reopening, merges and schema rebuilds never embed unchanged text, and `ReembedStale` after a model change. - Reranking: `IReranker` (a sibling of `IEmbedder`), `SearchQuery.Rerank(...)` as a stage over the best hits of any search (text, vector or hybrid) with the reranker's score and the first-stage score on each hit, `Explain` for the stage, `[FullText(Rerank = true)]` to rerank plain text searches by itself, the `rerank` property of query JSON, and `MiniLmReranker` in the models package (cross-encoder/ms-marco-MiniLM-L6-v2, Apache-2.0) with `WordPieceTokenizer.EncodePair`. - Hybrid search: `HybridQuery`, `SearchQuery.Hybrid(...)` and the `hybrid` forms of query JSON fuse a text arm and a vector arm by reciprocal rank fusion (default) or weighted linear fusion; filters apply to both arms. `Search(text)` is hybrid automatically when the type has one auto-embedded vector member and the index has an embedder. - Repository foundation: solution, shared build properties, packaging metadata, CI and release workflows. - Storage layer: a range-read interface with synchronous and asynchronous members, memory and local-file backends, a fault-injecting wrapper (torn, lost and reordered writes), and a block-transform slot. - Commit file format with a checksummed frame, and a crash-safe commit protocol, verified under seeded fault schedules. - Schema model with deterministic serialization, untyped documents, the analyzer pipeline contract with a reference analyzer, and the query, scorer, collector and segment-reader contracts. - Attribute types, the schema descriptor source generator, and shapes for `SearchIndex` and `SearchTool` (not implemented). - Dynamic JSON fields: a `[Dynamic]` property is stored whole and its leaf paths are indexed by kind (keyword, number, bool, date), filterable by path from LINQ (`Path`), filter strings and query JSON, within limits on depth, paths and lengths. - Schema evolution: opening an index with a changed schema rebuilds the segments that need it in the background from stored source, resumably, while the old schema keeps serving every segment; one commit makes the new schema visible on all of them; changes that cannot be converted fail at open naming the field. Commit format version 2 records the schema epoch and the rebuilt segments written ahead.