101 lines
4.7 KiB
Markdown
101 lines
4.7 KiB
Markdown
# Changelog
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All notable changes to Veritext will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [Unreleased]
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### Fixed
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- Fixed README example using incorrect property names (`grade_level` → `flesch_kincaid_grade`, `reading_ease` → `flesch_reading_ease`)
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- Fixed potential crash in ROUGE metric when all references are empty after tokenisation
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- Fixed potential division by zero in readability metric when text has no sentence endings
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- Fixed unbounded cache growth in `SemanticSimilarity` by implementing LRU eviction with configurable max size
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- Fixed mutable list aliasing in `AllOf` and `AnyOf` composite validators
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- Fixed regex pattern validation in `ContainsValidator` and `ExcludesValidator` to fail at init time rather than during `check()`
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### Added
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- Added `.score` property to `LexicalResult` for API consistency with other result types
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- Added `cache_max_size` parameter to `SemanticSimilarity` (default: 1000 embeddings)
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- Added test coverage for `core/config.py` and `core/logging.py` modules
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## [0.1.0] — 2026-02-03
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Initial release of Veritext, a semantic text validation framework for Python.
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### Added
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#### Core
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- Project scaffold with pyproject.toml and development tooling
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- Core exception hierarchy (`VeritextError` and subclasses)
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- Core types: `ValidationContext`, `CheckResult`, `ValidationResult`
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- Word tokeniser with Unicode normalisation support
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- Configuration module with pydantic-settings
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- Structured logging with structlog
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#### Metrics
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- Metrics module with `Metric` protocol, `AggregateStats`, and `BatchResult` types
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- BLEU metric implementation (BLEU-1 through BLEU-4 with brevity penalty)
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- ROUGE metric (ROUGE-1, ROUGE-2, ROUGE-L with precision/recall/F-measure)
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- Lexical similarity metric (Jaccard similarity and token overlap)
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- Flesch-Kincaid readability metrics (grade level and reading ease)
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- Batch scoring with aggregate statistics for all metrics
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#### Validators
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- Validators module with `Check` protocol for validation checks
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- Metric-based validators: `BleuValidator`, `RougeValidator`, `LexicalValidator`
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- Constraint validators: `LengthValidator`, `ReadabilityValidator`, `ContainsValidator`, `ExcludesValidator`
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- Composite validators: `AllOf` (all checks must pass), `AnyOf` (any check must pass)
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- Factory functions for clean validator API (`bleu()`, `rouge()`, `lexical()`, `length()`, `readability()`, `contains()`, `excludes()`, `all_of()`, `any_of()`)
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#### Semantic Similarity
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- Semantic similarity module with embedding-based text comparison (requires `veritext[semantic]` extra)
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- `SemanticSimilarity` metric using sentence-transformers for semantic relatedness
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- `SemanticValidator` for threshold-based semantic similarity validation
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- `semantic()` factory function for creating semantic validators
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- Embedding caching for performance optimisation in repeated comparisons
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#### Pytest Plugin
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- Native pytest plugin for CI/CD integration (entry point: `pytest11`)
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- `validate_text()` assertion function for expressive test assertions
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- `text_validation` marker for filtering validation tests
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- Pytest fixtures: `text_validator` factory and `validation_context` helper
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- Detailed failure messages with text preview and check diagnostics
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#### Benchmarking
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- Benchmark module for quality tracking and regression detection
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- `Benchmark` class for evaluating text quality over time with metric storage
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- `BenchmarkRun` and `RegressionReport` data models for tracking runs
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- SQLite storage backend with WAL mode for concurrent access
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- Rolling window baseline computation for historical comparison
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- `check_regression()` for statistical comparison against baseline
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- `assert_no_regression()` raises `RegressionDetectedError` for CI integration
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- Customisable tolerance threshold and window size for regression detection
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- Metadata support for tracking git SHA, model versions, etc.
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#### CLI
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- Command-line interface (CLI) via `veritext` command
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- `veritext validate` command for inline and file-based text validation
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- JSONL input format support for batch validation (`--file` option)
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- Separate candidate/reference file support (`--reference-file` option)
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- Multiple output formats: table (default), JSON, and simple text
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- `veritext benchmark run` command for running evaluations and storing results
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- `veritext benchmark show` command for viewing benchmark history
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- `veritext benchmark check` command for regression detection with exit code 1 on failure
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- Rich-formatted terminal output with tables and coloured panels
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#### Documentation
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- Comprehensive readme with usage examples
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- Example scripts: basic validation, chatbot testing, benchmark regression
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