v1.7.0
amirivojdan/shekarv1.7.0Sep 17, 2026by amirivojdan
Upgrading?
AI Summary
This release introduces unified batching across all ONNX models for improved performance, strengthens pipeline validation with robust error handling, and enhances classification and transliteration capabilities. It also features a significant expansion of the test suite and developer tooling improvements.
Key Highlights
- API-Compatible Batching: Unified interface across embeddings, NER, POS tagging, and transliteration models allowing bulk processing via list inputs.
- Enhanced Pipeline Validation: The `Pipeline` class now includes robust configuration validation and improved error handling for better debugging.
- Improved Informal Classification: The `RuleBasedInformalClassifier` features enhanced accuracy for detecting informal Persian text.
- Transliteration & Tokenizer Improvements: Better character-level encoding for `FarsiToTajik`/`TajikToFarsi` and ALBERT tokenizer performance boosts.
- Comprehensive Test Expansion: Added 400+ new test cases, including integration and unit tests for batching and validation.
New Features
- Unified batching interface supporting list inputs for multiple ONNX models.
- Robust validation and error handling for pipeline step configurations.
- Enhanced `RuleBasedInformalClassifier` for informal Persian text detection.
- Improved `FarsiToTajik` and `TajikToFarsi` transliteration accuracy.
- ALBERT tokenizer enhancements for better special token handling.
- Expanded test suite with 400+ new integration and unit tests.
Full Release Notes
# What's New in v1.7.0 This release brings unified batching across all ONNX models for efficient bulk processing, strengthened pipeline validation, improved classification accuracy, and enhanced transliteration capabilities. It also includes a comprehensive expansion of test coverage and developer tooling improvements. ## Highlights - **API-Compatible Batching Across ONNX Models** – added a unified batching interface across embeddings, NER, POS tagging, dependency parsing, and transliteration models. Process multiple inputs in a single API call for significant performance improvements. All models now accept lists of inputs and return batched results consistently (e.g., `embedder.embed(['متن اول', 'متن دوم'])` returns embeddings for both). - **Enhanced Pipeline Validation** – the `Pipeline` class now includes robust validation for step configuration, catching errors early with clear, actionable error messages. Improved error handling across all pipeline stages ensures better debugging and reliability in production workflows. - **Improved Rule-Based Informal Classification** – the `RuleBasedInformalClassifier` now features enhanced accuracy for detecting informal and colloquial Persian text through improved keyword matching and better conjugated verb form detection. - **Enhanced BYT5 Transliteration** – improvements to the `FarsiToTajik` and `TajikToFarsi` transliterators with better character-level encoding and decoding logic, resulting in more accurate transliteration of edge cases. - **ALBERT Tokenizer Enhancements** – improved ALBERT tokenizer performance with better handling of special tokens and improved tokenization accuracy across various Persian text formats. - **Comprehensive Test Suite Expansion** – added 400+ new test cases including: * 173 integration tests for batching contracts * 409 unit tests for batching validation * 51 pipeline-specific tests * Enhanced morphology and transliteration test coverage ## Other Changes - Minimum Python version remains **3.11+**. - Updated `ruff` to `0.16.1` for improved linting and code quality. - Improved GitHub Actions workflow configuration for better CI/CD reliability. - Expanded documentation and example notebooks covering new batching features.
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