24 Mar, 2026

2 commits

  • tangwang
     
  • The backend now exposes a structured debug_info that is much closer to
    the real ranking pipeline:
    
    query_analysis now includes index_languages, query_tokens, query-vector
    summary, translation/enrichment plan, and translation debug.
    query_build now explains the ES recall plan: base-language clause,
    translated clauses, filters vs post-filters, KNN settings,
    function-score config, and related inputs.
    es_request distinguishes the logical DSL from the actual body sent to
    ES, including rerank prefetch _source.
    es_response now includes the initial ES ranking window stats used for
    score interpretation.
    rerank now includes execution state, templates, rendered rerank query
    text, window/top_n, service/meta, and the fusion formula.
    pagination now shows rerank-window fetch vs requested page plus
    page-fill details.
    For each result in debug_info.per_result, ranking debug is now much
    richer:
    
    initial rank and final rank
    raw ES score
    es_score_normalized = raw score / initial ES window max
    es_score_norm = min-max normalization over the initial ES window
    explicit normalization notes explaining that fusion does not directly
    consume an ES-normalized score
    rerank input details: doc template, title suffix, template field values,
    doc preview/length
    fusion breakdown: rerank_factor, text_factor, knn_factor, constants, raw
    inputs, final fused score
    text subcomponents: source/translation/weighted/primary/support/fallback
    evidence via matched_queries
    richer style-intent SKU debug, including selected SKU summary and intent
    texts
    tangwang
     

23 Mar, 2026

1 commit


22 Mar, 2026

1 commit


20 Mar, 2026

2 commits

  • tangwang
     
  • ResultFormatter.format_search_results() runs.
    
    What changed:
    
    For each final paginated SPU hit, the searcher now scans
    skus[].option1_value against the query text set built from the original
    query, normalized query, rewritten query, and translations.
    If no option1_value matches textually, it falls back to embedding
    similarity and picks the SKU with the highest inner product against the
    query embedding.
    The matched SKU is promoted to the front of the SPU’s skus list.
    The SPU-level image_url is replaced with that matched SKU’s image_src.
    I left api/result_formatter.py unchanged because it already preserves
    the SKU order and reads image_url from _source; updating the page hits
    in searcher makes the formatter return the desired result automatically.
    
    Verification:
    
    ReadLints on the edited files: no errors
    Passed targeted tests:
    pytest tests/test_search_rerank_window.py -k "translated_query or
    no_direct_option_match"
    tangwang
     

18 Mar, 2026

1 commit

  • 核心改动在 rerank_client.py (line 99):fuse_scores_and_resort 现在按
    rerank * knn * text 的平滑乘法公式计算,优先从 hit["matched_queries"]
    里取 base_query 和 knn_query,并把 _text_score / _knn_score
    一并写回调试字段。为了让 KNN 也有名字,我给 top-level knn 加了 name:
    "knn_query",见 es_query_builder.py (line 273)。搜索执行时会在 rerank
    窗口内打开 include_named_queries_score,并在显式排序时加上
    track_scores,见 searcher.py (line 400) 和 es_client.py (line 224)。
    tangwang
     

13 Mar, 2026

1 commit


12 Mar, 2026

2 commits