{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/4"}],"enrichment":{"capability":"FlashRank re-ranks search results using lightweight cross-encoder and LLM-based models, optimized for speed and minimal resource overhead in retrieval pipelines.","skillfed_tags":["information-retrieval","ranking","rag"],"use_cases":["Improve LLM answer quality by re-ranking retrieval results before feeding them as context to an LLM","Reduce inference cost in serverless deployments by using a tiny reranker model instead of a large LLM for initial filtering","Re-rank multilingual search results using the ms-marco-MultiBERT-L-12 model for language support","Optimize retrieval latency by tuning max_length to match your typical passage+query token count","Fine-tune ranking for domain-specific queries using the ce-esci-MiniLM-L12-v2 model"],"what_it_does":"FlashRank is a Python library that re-ranks search results by scoring query-passage pairs using pre-trained cross-encoder and LLM models. It sits between your retrieval stage and LLM input, improving result quality without the overhead of full transformer inference. The library emphasizes minimal footprint\u2014the default model is ~4MB and runs on CPU\u2014making it suitable for serverless deployments and cost-sensitive environments.\n\nYou provide a query and a list of passages; FlashRank scores and sorts them by relevance. It supports multiple model sizes and types: tiny cross-encoders for speed, larger cross-encoders for precision, T5-based listwise rerankers for out-of-domain robustness, and multilingual variants. Runtime dependencies are lightweight (tokenizers, onnxruntime, numpy, requests, tqdm), and the library handles model downloading and caching automatically.","worth_installing":"Yes. FlashRank is actively maintained, has no known vulnerabilities, and offers a practical solution for improving search-to-LLM pipelines with minimal resource cost. Install it if you're building retrieval-augmented generation systems and want to improve result quality without adding significant latency or infrastructure overhead. The permissive Apache 2.0 license poses no restrictions."},"id":"flashrank","links":{"html":"https://skillfed.io/packages/flashrank","md":"https://skillfed.io/packages/flashrank.md","pypi":"https://pypi.org/project/flashrank/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-01-06","license_spdx":null,"license_treatment":"permissive","name":"FlashRank","python_support":"supports_current","summary":"Ultra lite & Super fast SoTA cross-encoder based re-ranking for your search & retrieval pipelines."},"popularity":{"monthly_downloads":770097,"position":5106,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.2.10"}