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feat: Add summary index for knowledge. (#31625)
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Jyong <76649700+JohnJyong@users.noreply.github.com> Co-authored-by: zxhlyh <jasonapring2015@outlook.com> Co-authored-by: Yansong Zhang <916125788@qq.com> Co-authored-by: hj24 <mambahj24@gmail.com> Co-authored-by: CodingOnStar <hanxujiang@dify.ai> Co-authored-by: CodingOnStar <hanxujiang@dify.com> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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@ -311,14 +311,18 @@ class IndexingRunner:
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qa_preview_texts: list[QAPreviewDetail] = []
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total_segments = 0
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# doc_form represents the segmentation method (general, parent-child, QA)
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index_type = doc_form
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index_processor = IndexProcessorFactory(index_type).init_index_processor()
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# one extract_setting is one source document
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for extract_setting in extract_settings:
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# extract
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processing_rule = DatasetProcessRule(
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mode=tmp_processing_rule["mode"], rules=json.dumps(tmp_processing_rule["rules"])
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)
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# Extract document content
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text_docs = index_processor.extract(extract_setting, process_rule_mode=tmp_processing_rule["mode"])
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# Cleaning and segmentation
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documents = index_processor.transform(
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text_docs,
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current_user=None,
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@ -361,6 +365,12 @@ class IndexingRunner:
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if doc_form and doc_form == "qa_model":
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return IndexingEstimate(total_segments=total_segments * 20, qa_preview=qa_preview_texts, preview=[])
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# Generate summary preview
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summary_index_setting = tmp_processing_rule.get("summary_index_setting")
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if summary_index_setting and summary_index_setting.get("enable") and preview_texts:
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preview_texts = index_processor.generate_summary_preview(tenant_id, preview_texts, summary_index_setting)
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return IndexingEstimate(total_segments=total_segments, preview=preview_texts)
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def _extract(
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