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Miscelleneous editorial updates (#5390)
### What problem does this PR solve? ### Type of change - [x] Documentation Update
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@ -258,10 +258,10 @@ export default {
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<i>This chunk method is automatically applied to all uploaded PPT files, so you do not need to specify it manually.</i></p>`,
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qa: `
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<p>
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This chunk method supports <b>EXCEL</b> and <b>CSV/TXT</b> file formats.
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This chunk method supports <b>XLSX</b> and <b>CSV/TXT</b> file formats.
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</p>
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<li>
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If a file is in <b>Excel</b> format, it should contain two columns
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If a file is in <b>XLSX</b> format, it should contain two columns
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without headers: one for questions and the other for answers, with the
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question column preceding the answer column. Multiple sheets are
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acceptable, provided the columns are properly structured.
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@ -281,7 +281,7 @@ export default {
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Résumés of various forms are parsed and organized into structured data to facilitate candidate search for recruiters.
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</p>
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`,
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table: `<p>Supported file formats are <b>EXCEL</b> and <b>CSV/TXT</b>.</p><p>
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table: `<p>Supported file formats are <b>XLSX</b> and <b>CSV/TXT</b>.</p><p>
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Here're some prerequisites and tips:
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<ul>
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<li>For CSV or TXT file, the delimiter between columns must be <em><b>TAB</b></em>.</li>
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@ -317,8 +317,8 @@ export default {
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<p>Knowlege base using 'Tag' as a chunking method is <b>NOT</b> supposed to be involved in RAG procedure.</p>
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<p>The chunks in this knowledge base are examples of tags, which demonstrate the entire tag set and the relevance between chunk and tags.</p>
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<p>This chunk method supports <b>EXCEL</b> and <b>CSV/TXT</b> file formats.</p>
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<p>If a file is in <b>Excel</b> format, it should contain two columns without headers: one for content and the other for tags, with the content column preceding the tags column. Multiple sheets are acceptable, provided the columns are properly structured.</p>
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<p>This chunk method supports <b>XLSX</b> and <b>CSV/TXT</b> file formats.</p>
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<p>If a file is in <b>XLSX</b> format, it should contain two columns without headers: one for content and the other for tags, with the content column preceding the tags column. Multiple sheets are acceptable, provided the columns are properly structured.</p>
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<p>If a file is in <b>CSV/TXT</b> format, it must be UTF-8 encoded with TAB as the delimiter to separate content and tags.</p>
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<p>In tags column, there're English <b>comma</b> between tags.</p>
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<i>Lines of texts that fail to follow the above rules will be ignored, and each pair will be considered a distinct chunk.</i>
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@ -352,16 +352,16 @@ The above is the content you need to summarize.`,
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searchTags: 'Search tags',
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tagCloud: 'Cloud',
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tagTable: 'Table',
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tagSet: 'Tag set',
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tagSet: 'Tag sets',
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tagSetTip: `
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<p> Selecting the 'Tag' knowledge bases helps to tag every chunks. </p>
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<p>Query to those chunks will also be with tags too.</p>
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This procedure will improve precision of retrieval by adding more information to the dataset, especially when there's a large set of chunks.
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<p>Difference between tags and keywords:</p>
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<p> Select one or multiple tag knowledge bases to auto-tag chunks in your knowledge base. </p>
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<p>The user query will also be auto-tagged.</p>
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This auto-tag feature enhances retrieval by adding another layer of domain-specific knowledge to the existing dataset.
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<p>Difference between auto-tag and auto-keyword:</p>
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<ul>
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<li>Tag is a close set which is defined and manipulated by user while keyword is an open set.</li>
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<li>You need to upload tag sets with samples prior to use.</li>
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<li>Keywords are generated by LLM which is expensive and time consuming.</li>
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<li>A tag knowledge base is a user-defined close set, whereas keywords extraced by the LLM can be regarded as an open set.</li>
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<li>You must upload tag sets in specified formats before running the auto-tag feature.</li>
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<li>The auto-keyword feature is dependent on the LLM and consumes a significant number of tokens.</li>
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</ul>
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`,
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topnTags: 'Top-N Tags',
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@ -420,7 +420,7 @@ This procedure will improve precision of retrieval by adding more information to
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language: 'Language',
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emptyResponse: 'Empty response',
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emptyResponseTip: `Set this as a response if no results are retrieved from the knowledge bases for your query, or leave this field blank to allow the LLM to improvise when nothing is found.`,
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emptyResponseMessage: `Empty response will be triggered when nothing relevant is retrieved from knowledge bases. Erase 'Empty response' since none of knowledge base is selected.`,
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emptyResponseMessage: `Empty response will be triggered when nothing relevant is retrieved from knowledge bases. You must clear the 'Empty response' field if no knowledge base is selected.`,
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setAnOpener: 'Opening greeting',
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setAnOpenerInitial: `Hi! I'm your assistant, what can I do for you?`,
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setAnOpenerTip: 'Set an opening greeting for users.',
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