veritext/changelog.md

Changelog

All notable changes to Veritext will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

Changed

• Refactored CLI metric computation to eliminate code duplication
• Version format updated from 0.1.0-dev to 0.1.0.dev0 (PEP 440 compliance)
• Settings instance is now cached via @lru_cache for better performance
• Documented composite validators' intentional deviation from Check protocol return type

Fixed

• Consolidated redundant empty checks in ROUGE-L computation
• Fixed README example using incorrect property names (grade_level → flesch_kincaid_grade, reading_ease → flesch_reading_ease)

Documentation

• Added Phase 10 (Portfolio Demos) to implementation plan: Streamlit demo and Jupyter notebooks
• Updated project plan with portfolio demo section
• Fixed potential crash in ROUGE metric when all references are empty after tokenisation
• Fixed potential division by zero in readability metric when text has no sentence endings
• Fixed unbounded cache growth in SemanticSimilarity by implementing LRU eviction with configurable max size
• Fixed mutable list aliasing in AllOf and AnyOf composite validators
• Fixed regex pattern validation in ContainsValidator and ExcludesValidator to fail at init time rather than during check()
• Fixed pytest plugin tests failing with duplicate plugin registration error

Added

• Added .score property to LexicalResult for API consistency with other result types
• Added cache_max_size parameter to SemanticSimilarity (default: 1000 embeddings)
• Added test coverage for core/config.py and core/logging.py modules

[0.1.0] — 2026-02-03

Initial release of Veritext, a semantic text validation framework for Python.

Added

Core

• Project scaffold with pyproject.toml and development tooling
• Core exception hierarchy (VeritextError and subclasses)
• Core types: ValidationContext, CheckResult, ValidationResult
• Word tokeniser with Unicode normalisation support
• Configuration module with pydantic-settings
• Structured logging with structlog

Metrics

• Metrics module with Metric protocol, AggregateStats, and BatchResult types
• BLEU metric implementation (BLEU-1 through BLEU-4 with brevity penalty)
• ROUGE metric (ROUGE-1, ROUGE-2, ROUGE-L with precision/recall/F-measure)
• Lexical similarity metric (Jaccard similarity and token overlap)
• Flesch-Kincaid readability metrics (grade level and reading ease)
• Batch scoring with aggregate statistics for all metrics

Validators

• Validators module with Check protocol for validation checks
• Metric-based validators: BleuValidator, RougeValidator, LexicalValidator
• Constraint validators: LengthValidator, ReadabilityValidator, ContainsValidator, ExcludesValidator
• Composite validators: AllOf (all checks must pass), AnyOf (any check must pass)
• Factory functions for clean validator API (bleu(), rouge(), lexical(), length(), readability(), contains(), excludes(), all_of(), any_of())

Semantic Similarity

• Semantic similarity module with embedding-based text comparison (requires veritext[semantic] extra)
• SemanticSimilarity metric using sentence-transformers for semantic relatedness
• SemanticValidator for threshold-based semantic similarity validation
• semantic() factory function for creating semantic validators
• Embedding caching for performance optimisation in repeated comparisons

Pytest Plugin

• Native pytest plugin for CI/CD integration (entry point: pytest11)
• validate_text() assertion function for expressive test assertions
• text_validation marker for filtering validation tests
• Pytest fixtures: text_validator factory and validation_context helper
• Detailed failure messages with text preview and check diagnostics

Benchmarking

• Benchmark module for quality tracking and regression detection
• Benchmark class for evaluating text quality over time with metric storage
• BenchmarkRun and RegressionReport data models for tracking runs
• SQLite storage backend with WAL mode for concurrent access
• Rolling window baseline computation for historical comparison
• check_regression() for statistical comparison against baseline
• assert_no_regression() raises RegressionDetectedError for CI integration
• Customisable tolerance threshold and window size for regression detection
• Metadata support for tracking git SHA, model versions, etc.

CLI

• Command-line interface (CLI) via veritext command
• veritext validate command for inline and file-based text validation
• JSONL input format support for batch validation (--file option)
• Separate candidate/reference file support (--reference-file option)
• Multiple output formats: table (default), JSON, and simple text
• veritext benchmark run command for running evaluations and storing results
• veritext benchmark show command for viewing benchmark history
• veritext benchmark check command for regression detection with exit code 1 on failure
• Rich-formatted terminal output with tables and coloured panels

Documentation

• Comprehensive readme with usage examples
• Example scripts: basic validation, chatbot testing, benchmark regression