Initial release v0.1.0

- Token-level differential privacy for LLMs
  - Integration with Document Privacy API
  - Comprehensive test suite and documentation
  - Examples and Jupyter notebook included

CHANGELOG.md

@@ -0,0 +1,37 @@
+# Changelog
+
+All notable changes to this project will be documented in this file.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
+and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+## [Unreleased]
+
+## [0.1.0] - 2025-01-01
+
+### Added
+
+- Initial release of DP-Fusion-Lib
+- `DPFusion` class for differentially private text generation
+  - Message-based context building with `add_message()`
+  - Direct context generation with `generate()`
+  - Token-level generation with `generate_from_tokens()`
+- `Tagger` class for automatic private phrase extraction
+  - Integration with Document Privacy API
+  - Support for multiple document types (HEALTH, FINANCE, LEGAL)
+- Privacy accounting functions
+  - `compute_epsilon_single_group()` for single-group privacy guarantees
+  - `compute_dp_epsilon()` for multi-group scenarios
+- Utility functions for advanced usage
+  - `compute_renyi_divergence_clipped_symmetric()` for divergence computation
+  - `find_lambda()` for binary search of mixing parameter
+  - `replace_sequences_with_placeholder_fast()` for token-level redaction
+- Support for HuggingFace transformers models
+- Incremental decoding with KV-cache optimization
+- Comprehensive documentation and examples
+
+### Dependencies
+
+- PyTorch >= 2.0.0
+- Transformers >= 4.25.0
+- Requests >= 2.25.0