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### What problem does this PR solve? Feat: Move the pipeline translation field to flow #9869 ### Type of change - [X] New Feature (non-breaking change which adds functionality)
This commit is contained in:
balibabu
@ -1605,6 +1605,119 @@ This delimiter is used to split the input text into several text pieces echo of
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ceateAgent: 'Agent flow',
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createPipeline: 'Ingestion pipeline',
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chooseAgentType: 'Choose Agent Type',
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parser: 'Parser',
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parserDescription:
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'Extracts raw text and structure from files for downstream processing.',
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tokenizer: 'Indexer',
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tokenizerRequired: 'Please add the Indexer node first',
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tokenizerDescription:
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'Transforms text into the required data structure (e.g., vector embeddings for Embedding Search) depending on the chosen search method.',
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splitter: 'Token',
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splitterDescription:
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'Split text into chunks by token length with optional delimiters and overlap.',
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hierarchicalMergerDescription:
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'Split documents into sections by title hierarchy with regex rules for finer control.',
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hierarchicalMerger: 'Title',
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extractor: 'Transformer',
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extractorDescription:
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'Use an LLM to extract structured insights from document chunks—such as summaries, classifications, etc.',
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outputFormat: 'Output format',
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fileFormats: 'File format',
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fileFormatOptions: {
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pdf: 'PDF',
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spreadsheet: 'Spreadsheet',
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image: 'Image',
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email: 'Email',
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'text&markdown': 'Text & Markup',
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word: 'Word',
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slides: 'PPT',
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audio: 'Audio',
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},
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fields: 'Field',
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addParser: 'Add Parser',
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hierarchy: 'Hierarchy',
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regularExpressions: 'Regular Expressions',
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overlappedPercent: 'Overlapped percent (%)',
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searchMethod: 'Search method',
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searchMethodTip: `Defines how the content can be searched — by full-text, embedding, or both.
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The Indexer will store the content in the corresponding data structures for the selected methods.`,
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// file: 'File',
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parserMethod: 'Parsing method',
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// systemPrompt: 'System Prompt',
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systemPromptPlaceholder:
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'Enter system prompt for image analysis, if empty the system default value will be used',
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exportJson: 'Export JSON',
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viewResult: 'View result',
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running: 'Running',
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summary: 'Summary',
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keywords: 'Keywords',
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questions: 'Questions',
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metadata: 'Metadata',
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fieldName: 'Result destination',
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prompts: {
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system: {
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keywords: `Role
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You are a text analyzer.
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Task
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Extract the most important keywords/phrases of a given piece of text content.
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Requirements
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- Summarize the text content, and give the top 5 important keywords/phrases.
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- The keywords MUST be in the same language as the given piece of text content.
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- The keywords are delimited by ENGLISH COMMA.
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- Output keywords ONLY.`,
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questions: `Role
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You are a text analyzer.
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Task
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Propose 3 questions about a given piece of text content.
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Requirements
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- Understand and summarize the text content, and propose the top 3 important questions.
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- The questions SHOULD NOT have overlapping meanings.
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- The questions SHOULD cover the main content of the text as much as possible.
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- The questions MUST be in the same language as the given piece of text content.
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- One question per line.
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- Output questions ONLY.`,
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summary: `Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.
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Key Instructions:
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1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.
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2. Language: Write the summary in the same language as the source text.
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3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.
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4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.`,
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metadata: `Extract important structured information from the given content. Output ONLY a valid JSON string with no additional text. If no important structured information is found, output an empty JSON object: {}.
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Important structured information may include: names, dates, locations, events, key facts, numerical data, or other extractable entities.`,
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},
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user: {
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keywords: `Text Content
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[Insert text here]`,
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questions: `Text Content
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[Insert text here]`,
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summary: `Text to Summarize:
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[Insert text here]`,
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metadata: `Content: [INSERT CONTENT HERE]`,
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},
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},
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cancel: 'Cancel',
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swicthPromptMessage:
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'The prompt word will change. Please confirm whether to abandon the existing prompt word?',
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tokenizerSearchMethodOptions: {
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full_text: 'Full-text',
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embedding: 'Embedding',
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},
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filenameEmbeddingWeight: 'Filename embedding weight',
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tokenizerFieldsOptions: {
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text: 'Processed Text',
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keywords: 'Keywords',
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questions: 'Questions',
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summary: 'Augmented Context',
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},
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imageParseMethodOptions: {
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ocr: 'OCR',
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},
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},
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llmTools: {
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bad_calculator: {
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@ -1705,125 +1818,6 @@ This delimiter is used to split the input text into several text pieces echo of
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<p>Are you sure you want to proceed?</p> `,
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unlinkPipelineModalConfirmText: 'Unlink',
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},
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dataflow: {
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parser: 'Parser',
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parserDescription:
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'Extracts raw text and structure from files for downstream processing.',
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tokenizer: 'Indexer',
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tokenizerRequired: 'Please add the Indexer node first',
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tokenizerDescription:
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'Transforms text into the required data structure (e.g., vector embeddings for Embedding Search) depending on the chosen search method.',
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splitter: 'Token',
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splitterDescription:
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'Split text into chunks by token length with optional delimiters and overlap.',
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hierarchicalMergerDescription:
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'Split documents into sections by title hierarchy with regex rules for finer control.',
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hierarchicalMerger: 'Title',
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extractor: 'Transformer',
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extractorDescription:
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'Use an LLM to extract structured insights from document chunks—such as summaries, classifications, etc.',
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outputFormat: 'Output format',
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lang: 'Language',
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fileFormats: 'File format',
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fileFormatOptions: {
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pdf: 'PDF',
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spreadsheet: 'Spreadsheet',
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image: 'Image',
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email: 'Email',
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'text&markdown': 'Text & Markup',
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word: 'Word',
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slides: 'PPT',
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audio: 'Audio',
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},
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fields: 'Field',
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addParser: 'Add Parser',
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hierarchy: 'Hierarchy',
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regularExpressions: 'Regular Expressions',
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overlappedPercent: 'Overlapped percent (%)',
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searchMethod: 'Search method',
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searchMethodTip: `Defines how the content can be searched — by full-text, embedding, or both.
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The Indexer will store the content in the corresponding data structures for the selected methods.`,
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begin: 'File',
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parserMethod: 'Parsing method',
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systemPrompt: 'System Prompt',
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systemPromptPlaceholder:
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'Enter system prompt for image analysis, if empty the system default value will be used',
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exportJson: 'Export JSON',
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viewResult: 'View result',
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running: 'Running',
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summary: 'Summary',
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keywords: 'Keywords',
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questions: 'Questions',
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metadata: 'Metadata',
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fieldName: 'Result destination',
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prompts: {
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system: {
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keywords: `Role
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You are a text analyzer.
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Task
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Extract the most important keywords/phrases of a given piece of text content.
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Requirements
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- Summarize the text content, and give the top 5 important keywords/phrases.
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- The keywords MUST be in the same language as the given piece of text content.
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- The keywords are delimited by ENGLISH COMMA.
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- Output keywords ONLY.`,
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questions: `Role
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You are a text analyzer.
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Task
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Propose 3 questions about a given piece of text content.
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Requirements
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- Understand and summarize the text content, and propose the top 3 important questions.
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- The questions SHOULD NOT have overlapping meanings.
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- The questions SHOULD cover the main content of the text as much as possible.
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- The questions MUST be in the same language as the given piece of text content.
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- One question per line.
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- Output questions ONLY.`,
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summary: `Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.
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Key Instructions:
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1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.
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2. Language: Write the summary in the same language as the source text.
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3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.
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4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.`,
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metadata: `Extract important structured information from the given content. Output ONLY a valid JSON string with no additional text. If no important structured information is found, output an empty JSON object: {}.
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Important structured information may include: names, dates, locations, events, key facts, numerical data, or other extractable entities.`,
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},
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user: {
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keywords: `Text Content
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[Insert text here]`,
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questions: `Text Content
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[Insert text here]`,
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summary: `Text to Summarize:
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[Insert text here]`,
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metadata: `Content: [INSERT CONTENT HERE]`,
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},
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},
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cancel: 'Cancel',
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swicthPromptMessage:
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'The prompt word will change. Please confirm whether to abandon the existing prompt word?',
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tokenizerSearchMethodOptions: {
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full_text: 'Full-text',
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embedding: 'Embedding',
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},
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filenameEmbeddingWeight: 'Filename embedding weight',
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tokenizerFieldsOptions: {
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text: 'Processed Text',
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keywords: 'Keywords',
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questions: 'Questions',
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summary: 'Augmented Context',
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},
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imageParseMethodOptions: {
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ocr: 'OCR',
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},
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note: 'Note',
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noteDescription: 'Note',
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notePlaceholder: 'Please enter a note',
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},
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datasetOverview: {
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downloadTip: 'Files being downloaded from data sources. ',
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processingTip: 'Files being processed by Ingestion pipeline.',
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