Text Embeddings and Rerank · agentsvc.io

Sentence embeddings (all-MiniLM-L6-v2, 384 dimensions, L2-normalized…

Multilingual input works best in English) for semantic search, clustering and deduplication, or rerank mode: pass query + documents to get documents sorted by cosine similarity. Runs locally, texts are not stored. Params: texts (1 to 32 strings, max 2000 chars each) for embed mode, or query + documents (up to 64) and top_k for rerank mode.