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feat: n to 1 retrieval legacy (#6554)
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@ -45,6 +45,29 @@ const translation = {
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},
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docsFailedNotice: 'documents failed to be indexed',
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retry: 'Retry',
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indexingTechnique: {
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high_quality: 'HQ',
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economy: 'ECO',
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},
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indexingMethod: {
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semantic_search: 'VECTOR',
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full_text_search: 'FULL TEXT',
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hybrid_search: 'HYBRID',
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},
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mixtureHighQualityAndEconomicTip: 'The Rerank model is required for mixture of high quality and economical knowledge bases.',
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inconsistentEmbeddingModelTip: 'The Rerank model is required if the Embedding models of the selected knowledge bases are inconsistent.',
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retrievalSettings: 'Retrieval Setting',
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rerankSettings: 'Rerank Setting',
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weightedScore: {
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title: 'Weighted Score',
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description: 'By adjusting the weights assigned, this rerank strategy determines whether to prioritize semantic or keyword matching.',
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semanticFirst: 'Semantic first',
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keywordFirst: 'Keyword first',
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customized: 'Customized',
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semantic: 'Semantic',
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keyword: 'Keyword',
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},
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nTo1RetrievalLegacy: 'According to product planning, N-to-1 retrieval will be officially deprecated in September. Until then you can still use it normally.',
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}
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export default translation
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@ -45,6 +45,29 @@ const translation = {
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},
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docsFailedNotice: '文档无法被索引',
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retry: '重试',
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indexingTechnique: {
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high_quality: '高质量',
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economy: '经济',
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},
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indexingMethod: {
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semantic_search: '向量检索',
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full_text_search: '全文检索',
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hybrid_search: '混合检索',
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},
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mixtureHighQualityAndEconomicTip: '混合使用高质量和经济型知识库需要配置 Rerank 模型。',
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inconsistentEmbeddingModelTip: '当所选知识库配置的 Embedding 模型不一致时,需要配置 Rerank 模型。',
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retrievalSettings: '召回设置',
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rerankSettings: 'Rerank 设置',
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weightedScore: {
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title: '权重设置',
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description: '通过调整分配的权重,重新排序策略确定是优先进行语义匹配还是关键字匹配。',
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semanticFirst: '语义优先',
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keywordFirst: '关键词优先',
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customized: '自定义',
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semantic: '语义',
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keyword: '关键词',
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},
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nTo1RetrievalLegacy: '根据产品规划,N 选 1 召回将于 9 月正式弃用。在那之前,您仍然可以正常使用它。',
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}
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export default translation
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