{"enrichment":{"capability":"Computes dense and sparse text embeddings, and reranking scores using pre-trained transformer models for semantic search, similarity, and information retrieval tasks.","verdict":"Production-ready embedding framework with no known vulnerabilities, active maintenance, and permissive Apache-2.0 licensing. Broad runtime dependency footprint (transformers, torch, numpy, scikit-learn, scipy, tokenizers, huggingface-hub, typing_extensions, tqdm) is standard for ML workloads; suitable for semantic search, retrieval, and reranking in research and production systems."},"id":"sentence-transformers","links":{"html":"https://skillfed.io/packages/sentence-transformers","md":"https://skillfed.io/packages/sentence-transformers.md","pypi":"https://pypi.org/project/sentence-transformers/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-06","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"sentence-transformers","python_support":"supports_current","summary":"Embeddings, Retrieval, and Reranking"},"popularity":{"tier":"top_1000"},"security":{"n_vulnerabilities":0},"version":"5.7.0"}