2584bd8c95
Two coherence rules added to DEFAULT_SYSTEM_PROMPT: - different values of the same type get distinct placeholders (context), e.g. old/new IBAN -> [PER_1.IBAN:Ancien] / [PER_1.IBAN:Nouveau] - never absorb adjacent punctuation/separators into a placeholder Took the live Gemma-4 (Infomaniak) e-learning demo from 4/5 to 5/5 exact round-trips. 36 tests passing. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
72 lines
4.1 KiB
Markdown
72 lines
4.1 KiB
Markdown
# Changelog
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All notable changes to this project are documented here. The format is based on
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[Keep a Changelog](https://keepachangelog.com/en/1.1.0/), and this project adheres to
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[Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [0.3.1] - Unreleased
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### Changed
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- Default prompt hardening for lossless round-trips: (1) two **different** values of the same type never
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share a placeholder — they must be distinguished by context (e.g. `[PER_1.IBAN:Ancien]` vs
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`[PER_1.IBAN:Nouveau]`), preventing a within-message collision (old/new IBAN); (2) the model must not
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absorb adjacent **punctuation/separators** (commas, spaces, parentheses) into a placeholder. Together
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these took the live Gemma-4 e-learning demo from 4/5 to 5/5 exact round-trips.
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## [0.3.0] - Unreleased
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### Changed
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- **`openAICompatibleProvider` now works with Infomaniak (and other open-model endpoints) out of the box.**
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`response_format` is **omitted by default** instead of hard-coding `{ type: 'json_object' }`, which
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current Infomaniak rejects (HTTP 422). Pass the new `responseFormat` option (e.g. `{ type: 'json_object' }`
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or a `json_schema` object) for endpoints that support/require it. **Breaking** for endpoints that relied
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on the previous forced `json_object`.
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- JSON responses are now **parsed leniently** — a fenced JSON code block or surrounding prose is tolerated
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(the outermost `{ … }` is extracted), so models without an enforced `response_format` don't cause
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spurious parse failures.
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- The default prompt gained a **COHÉRENCE** block (exact placeholder↔mapping-key identity, values are the
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original data never another placeholder, strict `[TYPE_N…]` format, mask the value not the adjacent
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label) to improve reliability across models.
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## [0.2.0] - Unreleased
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### Added
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- **`legend`** on every result — abbreviation → French meaning (`PER`→`Personne`, `M`→`Masculin`), safe to
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forward to a downstream LLM so it understands the placeholder tokens. Backed by a built-in
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`DEFAULT_LEGEND` so coverage is guaranteed even if the model omits entries.
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- The default prompt now lets the model **coin new uppercase abbreviations** for entities/attributes/
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context it discovers and return their meanings in `legende`.
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- `PatternDef.meaning` — optional human label for a tag, surfaced in the `legend`. `presets.swiss`/
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`presets.generic` ship French meanings.
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- `AnonymizationError` (exported) — thrown when anonymization can't complete and no fallback exists;
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carries the originating error in `.cause`.
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### Changed (breaking)
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- **Regex fallback is now opt-in.** `patterns` no longer defaults to `presets.swiss`. With no fallback,
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an LLM failure throws `AnonymizationError` (fail-closed) and the pre-filter is bypassed. At least one of
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`llm` or `patterns` is required, or the constructor throws.
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- `AnonymizationResult` gained a required `legend` field; `LlmProvider.anonymizeBatch` returns `legend`.
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- `anonymizeChunks(chunks, seed)` — `seed` is now `{ mapping, legend? }` (was the bare mapping) and the
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return includes `legend`.
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## [0.1.0] - Unreleased
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### Added
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- Initial public release.
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- `Anonymizer` — pre-filter → LLM → regex fallback, bidirectional validation, deterministic coreference,
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and de-collision across question and retrieved chunks (`anonymize`, `anonymizeChunks`, `deanonymize`).
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- `makeStreamDeanonymizer` — streaming-safe de-anonymization that never leaks a split placeholder.
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- `openAICompatibleProvider` — pluggable LLM detection over any OpenAI-compatible Chat Completions API.
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- `presets.swiss` and `presets.generic` regex pattern sets; fully configurable custom patterns.
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- Regex-only mode (no LLM provider required).
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- `PatternDef.validate` — optional second-stage predicate to cut false positives; `presets.generic` uses
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it for a Luhn check on credit-card candidates, and de-overlaps its phone/date/IP patterns.
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- `openAICompatibleProvider` retries transient failures (network/timeout/429/5xx) via `retries` and
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`retryDelayMs` options; non-transient 4xx and malformed responses are not retried.
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- Hardened the `nameHint` heuristic: `g`/`y` flags are stripped internally so `.test()` is stateless.
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