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* Preprocesses classifier content with Tantivy instead of NLTK Tokenizing and stemming now happen in one Rust call instead of NLTK's Python tokenizer and per word stemming, which also removes the Redis backed stem cache from every preprocessing call. The output matches the NLTK pipeline closely; tokens containing digits are now stemmed, and the English stop words follow Snowball's list. Stemming and stop word removal apply whenever the OCR language is one of the supported classifier languages, so PAPERLESS_ENABLE_NLTK and PAPERLESS_NLTK_DIR are removed. * Copies packages instead of hardlinking them in backend CI, some NLTK thing * Adds a normalization to NFC to better fit what Tantivy expects