24 Mar, 2026
3 commits
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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
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2, 漏了一些重要的stage,比如「款式意图 SKU 预筛选(StyleSkuSelector.prepare_hits)」,补上这个stage
20 Mar, 2026
3 commits
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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"
16 Mar, 2026
1 commit
13 Mar, 2026
3 commits
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2. 翻译限速 对应处理(qwen-mt限速)
12 Mar, 2026
1 commit
11 Mar, 2026
1 commit
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Made-with: Cursor
06 Mar, 2026
1 commit
04 Feb, 2026
1 commit
27 Jan, 2026
1 commit
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2. 返回query_normlized
24 Jan, 2026
1 commit
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2. 设置sku_filter_dimension参数的默认值为option1
27 Dec, 2025
1 commit
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修改内容 1. 在 tenant_facets_config.js 中添加映射配置 添加 TENANT_ID_MAPPING 配置对象,包含映射关系: 170 → 170 171 → 170 162 → 0 添加 getMappedTenantId() 函数,用于获取映射后的 tenant_id
25 Dec, 2025
1 commit
16 Dec, 2025
1 commit
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2. 搜索词挖掘
08 Dec, 2025
1 commit
03 Dec, 2025
1 commit
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{ "facets": [ { "field": "category1_name", "size": 15, "type": "terms" }, "specifications.color", "specifications.size" ] } { "facets": [ {"field": "category1_name", "size": 15, "type": "terms"}, {"field": "specifications.color", "size": 10, "type": "terms"}, {"field": "specifications.size", "size": 10, "type": "terms"} ] } 之前是上面的接口形式,主要是考虑 属性的分面, 因为 款式都是有限的 不需要设定 "size": 10, "type": "terms" 这些参数。 但是从接口设计层面,最好按下面这样,这样的话 specifications.color 和 category1_name 的组装格式 完全一样。前端不需要感知 属性分面 和 类别等其他字段分面的差异。
02 Dec, 2025
2 commits
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后端请求模型变更(api/models.py) SearchRequest.sku_filter_dimension 从 Optional[str] 改为 Optional[List[str]]。 语义:列表表示一个或多个“维度标签”,例如: 单维度:["color"]、["option1"] 多维度:["color", "size"]、["option1", "option2"] 描述更新为:对 维度组合进行分组,每个组合只保留一个 SKU。 结果格式化与去重逻辑(api/result_formatter.py) ResultFormatter.format_search_results(..., sku_filter_dimension: Optional[List[str]] = None),调用处已同步更新。 单维度旧逻辑升级为多维度逻辑: 新方法:_filter_skus_by_dimensions(skus, dimensions, option1_name, option2_name, option3_name, specifications)。 维度解析规则(按顺序处理,并去重): 若维度是 option1 / option2 / option3 → 对应 option1_value / option2_value / option3_value。 否则,将维度字符串转小写后,分别与 option1_name / option2_name / option3_name 对比,相等则映射到对应的 option*_value。 未能映射到任何字段的维度会被忽略。 对每个 SKU: 按解析出的字段列表(例如 ["option1_value", "option2_value"])取值,组成 key,如 ("red", "L");None 用空串 ""。 按 key 分组,每个 key 只保留遇到的第一个 SKU。 若列表为空或所有维度都无法解析,则 不做过滤,返回原始 skus。 Searcher 参数类型同步(search/searcher.py) Searcher.search(...) 中 sku_filter_dimension 参数类型从 Optional[str] 改为 Optional[List[str]]。 传给 ResultFormatter.format_search_results 时,直接传该列表。 前端参数格式调整(frontend/static/js/app.js) 输入框 #skuFilterDimension 依旧是一个文本框,但解析方式改为: 函数 getSkuFilterDimension(): 读取文本,如:"color" 或 "color,size" 或 "option1, color"。 用逗号 , 拆分,trim() 后过滤空串,返回 字符串数组,例如: "color" → ["color"] "color,size" → ["color", "size"] 若最终数组为空,则返回 null。 搜索请求体中仍使用字段名 sku_filter_dimension,但现在值是 string[] 或 null: body: JSON.stringify({ // ... sku_filter_dimension: skuFilterDimension, // 例如 ["color", "size"] debug: state.debug }) 文档更新(docs/搜索API对接指南.md) 请求体示例中的类型由: "sku_filter_dimension": "string" 改为: "sku_filter_dimension": ["string"] 参数表中: 从 string 改为 array[string],说明为“维度列表,按组合分组,每个组合保留一个 SKU”。 功能说明章节“SKU筛选维度 (sku_filter_dimension)”已调整为 列表语义 + 组合去重,并补充了示例: 单维度: { "query": "芭比娃娃", "sku_filter_dimension": ["color"] } 多维度组合: { "query": "芭比娃娃", "sku_filter_dimension": ["color", "size"] } 使用方式总结 单维度去重(保持旧行为的等价写法) 旧:"sku_filter_dimension": "color" 新:"sku_filter_dimension": ["color"] 多维度组合去重(你新提的需求) 例如希望“每个 SPU 下,同一颜色+尺码组合只保留一个 SKU”: { "query": "芭比娃娃", "sku_filter_dimension": ["color", "size"] } -
sku_filter_dimension=color sku_filter_dimension=option1 / option2 /option3 以上两种方式都可以
01 Dec, 2025
1 commit
29 Nov, 2025
1 commit
14 Nov, 2025
3 commits
13 Nov, 2025
3 commits
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创建统一配置文件 config/config.yaml(从 base 配置迁移,移除 customer_name) 创建脚本体系 启动、停止、重启、moc数据到mysql、从mysql灌入数据到ES 这些脚本 restart.sh run.sh 内部调用 启动前后端 scripts/mock_data.sh mock数据 -> mysql scripts/ingest.sh mysql->ES
12 Nov, 2025
1 commit
11 Nov, 2025
4 commits
10 Nov, 2025
1 commit
08 Nov, 2025
2 commits