• Breaking change: Drop Python 3.8 and 3.9 support. Minimum required version is now Python 3.10.
• Add Python 3.12 support.
• Add compatibility with Intel GPUs and other Torch acceleration devices.
• Remove numpy<2.0.0 version cap to support NumPy 2.x.
• Bump pinned dependency versions for Python 3.12+ compatibility (unpin uvicorn, python-decouple, pylint-django, pre-commit, pycountry).
• Update CI/CD workflows, documentation, and package setup for Python 3.12.
• Fix outdated model download URLs from graal.ift.ulaval.ca to HuggingFace Hub.
• Remove unused BASE_URL constant.
• Add missing parameterized type hints across the codebase (List[str], Dict[str, int], List[Callable], etc.).
• Add missing return type annotations to multiple functions and methods.
• Add Python 3.13 support.
• Make fasttext-wheel an optional dependency. On Python 3.13+ (or when fasttext is not installed), Deepparse
  automatically falls back to Gensim's load_facebook_vectors to load FastText embeddings. Install with
  pip install deepparse[fasttext] for native FastText support on Python 3.10–3.12.
• Fix FastTextEmbeddingsModel.dim property to use vector_size when using the Gensim fallback.
• Fix Python version in deploy.yml and python-publish.yml workflows (was set to non-existent 3.14).
• Update GitHub Actions to latest major versions (checkout@v4, setup-python@v5, codeql-action@v3, gh-pages@v4).
• Fix Dependabot target branch from non-existent develop to dev.
• Remove dead code: unused attention_output tensor allocation in Seq2SeqModel._decoder_step.
• Fix download_fasttext_magnitude_embeddings always re-downloading even when cached.
• Replace assert statements with HTTPException in FastAPI app for proper error handling.
• Change default logging level from DEBUG to WARNING in app module.
• Remove unnecessary pybind11 from build-system requirements.
• Remove obsolete "temporary fix for torch 1.6" comments in encoder, decoder and embedding network.
• Remove deprecated version key from docker-compose.yml.
• Fix mixed f-string/%-formatting in download progress bar.
• Update Dockerfile base images to PyTorch 2.5.1 / CUDA 12.4 and Python 3.13.
• Migrate PyPI publish workflow from deprecated setup.py sdist bdist_wheel to python -m build.
• Add MANIFEST.in to ensure version.txt and README.md are included in source distributions.
• Restrict docs workflow to only build on main, dev, and stable branches.
• Bump actions/setup-python from v5 to v6.
• Bump docker/metadata-action from 4.3.0 to 5.10.0.
• Bump docker/build-push-action from 4.0.0 to 6.19.2.
• Bump github/codeql-action from v3 to v4.
• Bump actions/first-interaction from v1 to v3.
• Bump fastapi[all] from 0.109.1 to 0.134.0.

• Switch model weights hosting to hugging face

0.9.13

Fix dependency issues with Gensim and Scipy versions.

0.9.12

• Bug-fix the call to the BPEmb class instead of the BPEmbBaseURLWrapperBugFix to fix the download URL in download_models.

0.9.11

• Fix Sentry version error in Docker Image.

• Fix and improve documentation.
• Remove fixed dependencies version.
• Fix app errors.
• Add data validation for 1) multiple consecutive whitespace and 2) newline.
• Fixes some errors in tests.
• Add an argument to the DatasetContainer interface to use a pre-processing data cleaning function before validation.
• Hot-fix the issue with the BPEmb base URL download problem. See issue 221.
• Fix the NumPy version due to a major release with breaking changes.
• Fix the SciPy version due to breaking change with Gensim.
• Fix circular import in the API app.
• Fix deprecated max_request_body_size in Sentry.

• Add version to Seq2Seq and AddressParser.
• Add a Deepparse as an API using FastAPI.
• Add a Dockerfile and a docker-compose.yml to build a Docker container for the API.
• Bug-fix the default pre-processors that were not all apply but only the last one.

• Hot-Fix wheel install (See issue 196).

• New models release with more meta-data.
• Add a feature to use an AddressParser from a URI.
• Add a feature to upload the trained model to a URI.
• Add an example of how to use URI for parsing from and uploading to.
• Improve error handling of path_to_retrain_model.
• Bug-fix pre-processor error.
• Add verbose override and improve verbosity handling in retrain.
• Bug-fix the broken FastText installation using fasttext-wheel instead of fasttext (
  see here
  and here).

• Add Python 3.11.
• Add pre-processor when parsing addresses.
• Add pin_memory=True when using a CUDA device to increase performance as suggested
• by Torch documentation.
• Add torch.no_grad() context manager in call() to increase performance.
• Reduce memory swap between CPU and GPU by instantiating Tensor directly on the GPU device.
• Improve some Warnings clarity (i.e. category and message).
• Bug-fix MacOS multiprocessing. It was impossible to use in multiprocess since we were not testing whether torch
• multiprocess was set properly. Now, we set it properly and raise a warning instead of an error.
• Drop Python 3.7 support since newer Python versions are faster
• and Torch 2.0 does not support Python 3.7.
• Improve error handling with wrong checkpoint loading in AddressParser retrain_path use.
• Add torch.compile integration to improve performance (Torch 1.x still supported) with mode="reduce-overhead" as
• suggested in the documentation. It
• increases the performance by about 1/100.