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diff --git a/python-top2vec.spec b/python-top2vec.spec new file mode 100644 index 0000000..bab414d --- /dev/null +++ b/python-top2vec.spec @@ -0,0 +1,124 @@ +%global _empty_manifest_terminate_build 0 +Name: python-top2vec +Version: 1.0.29 +Release: 1 +Summary: Top2Vec learns jointly embedded topic, document and word vectors. +License: BSD +URL: https://github.com/ddangelov/Top2Vec +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/55/92/8ab9d43de0437c6ec1bf8dcd2f0da484b4c78ed18c4dd189c52e5a26e0a1/top2vec-1.0.29.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-pandas +Requires: python3-scikit-learn +Requires: python3-gensim +Requires: python3-umap-learn +Requires: python3-hdbscan +Requires: python3-wordcloud +Requires: python3-hnswlib +Requires: python3-tensorflow +Requires: python3-tensorflow-hub +Requires: python3-tensorflow-text +Requires: python3-torch +Requires: python3-sentence-transformers + +%description +Top2Vec is an algorithm for **topic modeling** and **semantic search**. It automatically detects topics present in text +and generates jointly embedded topic, document and word vectors. Once you train the Top2Vec model +you can: +* Get number of detected topics. +* Get topics. +* Get topic sizes. +* Get hierarchichal topics. +* Search topics by keywords. +* Search documents by topic. +* Search documents by keywords. +* Find similar words. +* Find similar documents. +* Expose model with [RESTful-Top2Vec](https://github.com/ddangelov/RESTful-Top2Vec) +See the [paper](http://arxiv.org/abs/2008.09470) for more details on how it works. + +%package -n python3-top2vec +Summary: Top2Vec learns jointly embedded topic, document and word vectors. +Provides: python-top2vec +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-top2vec +Top2Vec is an algorithm for **topic modeling** and **semantic search**. It automatically detects topics present in text +and generates jointly embedded topic, document and word vectors. Once you train the Top2Vec model +you can: +* Get number of detected topics. +* Get topics. +* Get topic sizes. +* Get hierarchichal topics. +* Search topics by keywords. +* Search documents by topic. +* Search documents by keywords. +* Find similar words. +* Find similar documents. +* Expose model with [RESTful-Top2Vec](https://github.com/ddangelov/RESTful-Top2Vec) +See the [paper](http://arxiv.org/abs/2008.09470) for more details on how it works. + +%package help +Summary: Development documents and examples for top2vec +Provides: python3-top2vec-doc +%description help +Top2Vec is an algorithm for **topic modeling** and **semantic search**. It automatically detects topics present in text +and generates jointly embedded topic, document and word vectors. Once you train the Top2Vec model +you can: +* Get number of detected topics. +* Get topics. +* Get topic sizes. +* Get hierarchichal topics. +* Search topics by keywords. +* Search documents by topic. +* Search documents by keywords. +* Find similar words. +* Find similar documents. +* Expose model with [RESTful-Top2Vec](https://github.com/ddangelov/RESTful-Top2Vec) +See the [paper](http://arxiv.org/abs/2008.09470) for more details on how it works. + +%prep +%autosetup -n top2vec-1.0.29 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-top2vec -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.29-1 +- Package Spec generated |