mirror of
https://github.com/infiniflow/ragflow.git
synced 2025-12-08 12:32:30 +08:00
493 lines
25 KiB
JSON
493 lines
25 KiB
JSON
{
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"id": 24,
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"title": {
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"en": "Chunk Summary",
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"zh": "总结切片"
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},
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"description": {
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"en": "This template uses an LLM to generate chunk summaries for building text and vector indexes. During retrieval, summaries enhance matching, and the original chunks are returned as results.",
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"zh": "此模板利用大模型生成切片摘要，并据此建立全文索引与向量。检索时以摘要提升匹配效果，最终召回对应的原文切片。"
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},
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"canvas_type": "Ingestion Pipeline",
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"canvas_category": "dataflow_canvas",
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"dsl": {
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"components": {
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"File": {
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"obj": {
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"component_name": "File",
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"params": {}
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},
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"downstream": [
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"Parser:HipSignsRhyme"
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],
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"upstream": []
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},
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"Parser:HipSignsRhyme": {
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"obj": {
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"component_name": "Parser",
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"params": {
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"outputs": {
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"html": {
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"type": "string",
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"value": ""
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},
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"json": {
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"type": "Array<object>",
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"value": []
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},
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"markdown": {
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"type": "string",
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"value": ""
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},
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"text": {
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"type": "string",
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"value": ""
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}
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},
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"setups": {
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"pdf": {
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"output_format": "json",
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"suffix": [
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"pdf"
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],
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"parse_method": "DeepDOC"
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},
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"spreadsheet": {
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"output_format": "html",
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"suffix": [
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"xls",
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"xlsx",
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"csv"
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]
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},
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"image": {
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"output_format": "text",
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"suffix": [
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"jpg",
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"jpeg",
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"png",
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"gif"
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],
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"parse_method": "ocr"
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},
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"email": {
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"output_format": "text",
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"suffix": [
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"eml",
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"msg"
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],
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"fields": [
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"from",
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"to",
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"cc",
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"bcc",
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"date",
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"subject",
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"body",
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"attachments"
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]
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},
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"text&markdown": {
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"output_format": "text",
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"suffix": [
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"md",
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"markdown",
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"mdx",
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"txt"
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]
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},
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"word": {
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"output_format": "json",
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"suffix": [
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"doc",
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"docx"
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]
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},
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"slides": {
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"output_format": "json",
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"suffix": [
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"pptx"
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]
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}
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}
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}
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},
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"downstream": [
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"Splitter:LateExpertsFeel"
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],
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"upstream": [
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"File"
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]
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},
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"Splitter:LateExpertsFeel": {
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"obj": {
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"component_name": "Splitter",
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"params": {
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"chunk_token_size": 512,
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"delimiters": [
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"\n"
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],
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"outputs": {
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"chunks": {
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"type": "Array<Object>",
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"value": []
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}
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},
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"overlapped_percent": 0
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}
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},
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"downstream": [
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"Extractor:YummyGhostsType"
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],
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"upstream": [
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"Parser:HipSignsRhyme"
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]
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},
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"Tokenizer:EightRocketsAppear": {
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"obj": {
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"component_name": "Tokenizer",
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"params": {
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"fields": "summary",
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"filename_embd_weight": 0.1,
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"outputs": {},
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"search_method": [
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"embedding",
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"full_text"
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]
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}
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},
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"downstream": [],
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"upstream": [
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"Extractor:YummyGhostsType"
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]
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},
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"Extractor:YummyGhostsType": {
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"obj": {
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"component_name": "Extractor",
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"params": {
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"field_name": "summary",
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"frequencyPenaltyEnabled": false,
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"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat@DeepSeek",
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"maxTokensEnabled": false,
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"max_tokens": 256,
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"outputs": {
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"chunks": {
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"type": "Array<Object>",
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"value": []
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}
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},
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"presencePenaltyEnabled": false,
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"presence_penalty": 0.4,
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"prompts": [
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{
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"content": "Text to Summarize:\n\n\n{Splitter:LateExpertsFeel@chunks}",
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"role": "user"
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}
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],
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"sys_prompt": "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.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.",
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"temperature": 0.1,
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"temperatureEnabled": false,
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"topPEnabled": false,
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"top_p": 0.3
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}
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},
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"downstream": [
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"Tokenizer:EightRocketsAppear"
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],
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"upstream": [
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"Splitter:LateExpertsFeel"
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]
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}
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},
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"globals": {},
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"graph": {
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"nodes": [
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{
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"data": {
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"label": "File",
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"name": "File"
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},
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"id": "File",
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"measured": {
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"height": 48,
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"width": 200
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},
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"position": {
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"x": 50,
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"y": 200
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},
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"sourcePosition": "left",
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"targetPosition": "right",
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"type": "beginNode"
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},
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{
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"data": {
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"form": {
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"outputs": {
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"html": {
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"type": "string",
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"value": ""
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},
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"json": {
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"type": "Array<object>",
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"value": []
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},
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"markdown": {
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"type": "string",
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"value": ""
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},
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"text": {
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"type": "string",
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"value": ""
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}
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},
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"setups": [
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{
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"fileFormat": "pdf",
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"output_format": "json",
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"parse_method": "DeepDOC"
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},
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{
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"fileFormat": "spreadsheet",
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"output_format": "html"
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},
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{
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"fileFormat": "image",
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"output_format": "text",
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"parse_method": "ocr"
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},
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{
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"fields": [
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"from",
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"to",
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"cc",
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"bcc",
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"date",
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"subject",
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"body",
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"attachments"
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],
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"fileFormat": "email",
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"output_format": "text"
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},
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{
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"fileFormat": "text&markdown",
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"output_format": "text"
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},
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{
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"fileFormat": "word",
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"output_format": "json"
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},
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{
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"fileFormat": "slides",
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"output_format": "json"
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}
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]
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},
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"label": "Parser",
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"name": "Parser"
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},
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"dragging": false,
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"id": "Parser:HipSignsRhyme",
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"measured": {
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"height": 412,
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"width": 200
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},
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"position": {
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"x": 316.99524094206413,
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"y": 195.39629819663406
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},
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"selected": false,
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"sourcePosition": "right",
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"targetPosition": "left",
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"type": "parserNode"
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},
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{
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"data": {
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"form": {
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"chunk_token_size": 512,
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"delimiters": [
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{
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"value": "\n"
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}
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],
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"outputs": {
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"chunks": {
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"type": "Array<Object>",
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"value": []
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}
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},
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"overlapped_percent": 0
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},
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"label": "Splitter",
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"name": "Token Splitter"
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},
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"dragging": false,
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"id": "Splitter:LateExpertsFeel",
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"measured": {
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"height": 80,
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"width": 200
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},
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"position": {
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"x": 600.5891036507014,
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"y": 197.6804920892271
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},
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"selected": false,
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"sourcePosition": "right",
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"targetPosition": "left",
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"type": "splitterNode"
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},
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{
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"data": {
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"form": {
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"fields": "summary",
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"filename_embd_weight": 0.1,
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"outputs": {},
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"search_method": [
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"embedding",
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"full_text"
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]
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},
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"label": "Tokenizer",
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"name": "Tokenizer"
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},
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"dragging": false,
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"id": "Tokenizer:EightRocketsAppear",
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"measured": {
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"height": 120,
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"width": 200
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},
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"position": {
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"x": 1136.0745258879847,
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"y": 202.22674640530906
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},
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"selected": false,
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"sourcePosition": "right",
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"targetPosition": "left",
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"type": "tokenizerNode"
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},
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{
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"data": {
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"form": {
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"field_name": "summary",
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"frequencyPenaltyEnabled": false,
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"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat@DeepSeek",
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"maxTokensEnabled": false,
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"max_tokens": 256,
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"outputs": {
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"chunks": {
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"type": "Array<Object>",
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"value": []
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}
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},
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"presencePenaltyEnabled": false,
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"presence_penalty": 0.4,
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"prompts": "Text to Summarize:\n\n\n{Splitter:LateExpertsFeel@chunks}",
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"sys_prompt": "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.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.",
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"temperature": 0.1,
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"temperatureEnabled": false,
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"topPEnabled": false,
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"top_p": 0.3
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},
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"label": "Extractor",
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"name": "Transformer"
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},
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"dragging": false,
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"id": "Extractor:YummyGhostsType",
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"measured": {
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"height": 84,
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"width": 200
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},
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"position": {
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"x": 870.1728208672672,
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"y": 201.4516837225608
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},
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"selected": false,
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"sourcePosition": "right",
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"targetPosition": "left",
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"type": "contextNode"
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},
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{
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"id": "Note:MightyPandasWatch",
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"type": "noteNode",
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"position": {
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"x": 1128.1996486833773,
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"y": 342.4601052720091
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},
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"data": {
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"label": "Note",
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"name": "Index summary",
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"form": {
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"text": "Using summary to build both text and vector indexes."
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}
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},
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"sourcePosition": "right",
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"targetPosition": "left",
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"dragHandle": ".note-drag-handle",
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"measured": {
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"width": 249,
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"height": 128
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},
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"selected": false,
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"dragging": false
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}
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],
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"edges": [
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{
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"data": {
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"isHovered": false
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},
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"id": "xy-edge__Filestart-Parser:HipSignsRhymeend",
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"source": "File",
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"sourceHandle": "start",
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"target": "Parser:HipSignsRhyme",
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"targetHandle": "end"
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},
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{
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"data": {
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"isHovered": false
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},
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"id": "xy-edge__Parser:HipSignsRhymestart-Splitter:LateExpertsFeelend",
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"source": "Parser:HipSignsRhyme",
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"sourceHandle": "start",
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"target": "Splitter:LateExpertsFeel",
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"targetHandle": "end"
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},
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{
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"data": {
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"isHovered": false
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},
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"id": "xy-edge__Splitter:LateExpertsFeelstart-Extractor:YummyGhostsTypeend",
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"source": "Splitter:LateExpertsFeel",
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"sourceHandle": "start",
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"target": "Extractor:YummyGhostsType",
|
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"targetHandle": "end"
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},
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{
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"data": {
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"isHovered": false
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},
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"id": "xy-edge__Extractor:YummyGhostsTypestart-Tokenizer:EightRocketsAppearend",
|
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"markerEnd": "logo",
|
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"source": "Extractor:YummyGhostsType",
|
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"sourceHandle": "start",
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"style": {
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"stroke": "rgba(91, 93, 106, 1)",
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"strokeWidth": 1
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},
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"target": "Tokenizer:EightRocketsAppear",
|
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"targetHandle": "end",
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"type": "buttonEdge",
|
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"zIndex": 1001
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}
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|
]
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},
|
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"history": [],
|
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"messages": [],
|
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"path": [],
|
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"retrieval": []
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},
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"avatar": 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8rlicJe8+ZPcbxKVaFdMBU4XMeZcbJTcbrwXw34ATX1SYj72NK4kJcssiS4czSDDjVeOzW2M9qM19rcfMsFTQvCc6uC72td1HwR3pdbvt7cyceqLj2Knz6Br2qRRUvMtBesn6S4l3xd7i6CK6MkrVPcYa3bEfN/mJrlNPTyFIb9hJBf/O3fQ3B6D7564aoAAAAASUVORK5CYII="
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