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retrieval-and-utilities

retrieval-and-utilities

Dense semantic search utilities, retrieve-and-rerank orchestration, hard-negative mining, embedding quantization, similarity helpers, corpus chunking, and vector DB/service cautions for sentence-transformers.

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name: retrieval-and-utilities description: "Dense semantic search utilities, retrieve-and-rerank orchestration, hard-negative mining, embedding quantization, similarity helpers, corpus chunking, and vector DB/service cautions for sentence-transformers." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Retrieval and Utilities

Use this sub-skill when a task asks for dense retrieval, semantic search over precomputed embeddings, a retrieve-then-rerank handoff, hard-negative mining, embedding quantization for retrieval, paraphrase/community utilities, or similarity helper selection.

Route the task

  • For dense top-k search over embeddings, use sentence_transformers.util.semantic_search; see references/api-reference.md.
  • For two-stage retrieval, first preserve corpus_id from dense hits, then hand the selected texts and IDs to a CrossEncoder; see references/retrieval-reference.md.
  • For dataset construction, use sentence_transformers.util.mine_hard_negatives with explicit dataset column names, output format, and score/margin filters.
  • For memory or latency pressure, tune query_chunk_size, corpus_chunk_size, top_k, embedding precision, and optional FAISS/USearch/vector DB integration.
  • For cosine/dot/euclidean/manhattan behavior, paraphrase mining, community detection, and quantized embedding search, use the API notes before writing code.

Boundaries

  • Low-level SentenceTransformer.encode choices belong in ../embeddings-and-similarity/SKILL.md.
  • CrossEncoder constructor, prediction, ranking, and activation details belong in ../reranking-cross-encoder/SKILL.md.
  • SparseEncoder-specific search belongs in ../sparse-encoder-search/SKILL.md.
  • Training losses and evaluators belong in ../evaluation-and-training/SKILL.md.

Fast checks

  • Run python scripts/semantic_search_demo.py --help to inspect the safe demo CLI.
  • Run python scripts/semantic_search_demo.py --toy-tensors for a network-free semantic search example.
  • Use python scripts/semantic_search_demo.py --model MODEL_NAME_OR_PATH --local-files-only only when the model is already available locally.

References

  • API contracts: references/api-reference.md
  • Retrieval workflows: references/retrieval-reference.md
  • Failure modes: references/troubleshooting.md
  • Demo script: scripts/semantic_search_demo.py
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