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效率与协作 · SKILL.md

similarity-search

similarity-search

【效率与协作】Score text pairs and run dense or BM25 retrieval with text2vec.

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技能说明

GitHub

name: similarity-search description: "Score text pairs and run dense or BM25 retrieval with text2vec." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Similarity Search

Use this sub-skill when you need sentence similarity, pair scoring, semantic search, or lexical BM25 retrieval in text2vec.

Route here for

  • Pairwise similarity with Similarity, SimilarityType, EmbeddingType, get_score, get_scores, and similarity.
  • Dense retrieval helpers with cos_sim and semantic_search for tensor or NumPy embeddings.
  • Raw-text BM25 retrieval with Jieba segmentation and top-k ranking.
  • Aligned pair scoring from JSONL, CSV, or TSV without accidentally building a full cross-product matrix.
  • Query-to-corpus retrieval workflows where you want either no-network BM25 now or dense search from cached embeddings later.

Do not handle here

  • Embedding initialization, batch vector generation, or CLI embedding export: route to embeddings.
  • Fine-tuning, training data validation, and negative mining: route to training-finetuning.
  • Benchmark-style model quality evaluation and leaderboard comparison: route to evaluation-benchmarks.
  • HTTP serving, FastAPI, Jina, or Gradio deployment: route to serving-deployment.

Operating workflow

  1. Decide whether the task is pair scoring or retrieval.
  2. For pair scoring, choose vector-only scoring or model-backed scoring.
  3. For retrieval, choose BM25 when you want a no-network lexical path, or dense search when you already have embeddings or a cached model.
  4. Read the API shapes in references/api-reference.md.
  5. Use the bundled helpers in scripts/ for safe JSONL/CSV/TSV workflows.
  6. Check references/troubleshooting.md if scores, shapes, or downloads look wrong.

Bundled scripts

Start with references/workflows.md for ready-to-run patterns and references/api-reference.md for return shapes.

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