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{
"id" : 24 ,
"title" : {
"en" : "Chunk Summary" ,
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"de" : "Segmentzusammenfassung" ,
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"zh" : "总结切片"
} ,
"description" : {
"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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"de" : "Diese Vorlage nutzt ein LLM zur Generierung von Segmentzusammenfassungen für den Aufbau von Text- und Vektorindizes. Bei der Abfrage verbessern die Zusammenfassungen die Übereinstimmung, während die ursprünglichen Segmente als Ergebnisse zurückgegeben werden." ,
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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。"
} ,
"canvas_type" : "Ingestion Pipeline" ,
"canvas_category" : "dataflow_canvas" ,
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"dsl" : {
"components" : {
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"Extractor:SharpTaxisSay" : {
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"downstream" : [
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"Tokenizer:ShaggyShrimpsLose"
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] ,
"obj" : {
"component_name" : "Extractor" ,
"params" : {
"field_name" : "summary" ,
"frequencyPenaltyEnabled" : true ,
"frequency_penalty" : 0.7 ,
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"llm_id" : "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW" ,
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"maxTokensEnabled" : false ,
"max_tokens" : 256 ,
"outputs" : {
"chunks" : {
"type" : "Array<Object>" ,
"value" : [ ]
}
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} ,
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"presencePenaltyEnabled" : true ,
"presence_penalty" : 0.4 ,
"prompts" : [
{
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"content" : "Text to Summarize:\n{TokenChunker:ModernPetsKneel@chunks}" ,
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"role" : "user"
}
] ,
"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." ,
"temperature" : 0.1 ,
"temperatureEnabled" : true ,
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"tenant_llm_id" : 63 ,
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"topPEnabled" : true ,
"top_p" : 0.3
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}
} ,
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"upstream" : [
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"TokenChunker:ModernPetsKneel"
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]
} ,
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] ,
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"params" : { }
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} ,
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} ,
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"Parser:HipSignsRhyme" : {
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"TokenChunker:ModernPetsKneel"
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] ,
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"outputs" : {
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"value" : ""
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} ,
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} ,
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} ,
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"image" : {
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"flatten_media_to_text" : false ,
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]
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}
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}
}
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} ,
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"upstream" : [
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]
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} ,
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"downstream" : [
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"Extractor:SharpTaxisSay"
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] ,
"obj" : {
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"params" : {
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"chunk_token_size" : 512 ,
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"delimiter_mode" : "token_size" ,
"delimiters" : [ ] ,
"image_context_size" : 0 ,
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"outputs" : {
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} ,
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"overlapped_percent" : 0 ,
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}
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} ,
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} ,
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"filename_embd_weight" : 0.1 ,
"outputs" : { } ,
"search_method" : [
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]
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}
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} ,
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]
}
} ,
"globals" : {
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"sys.history" : [ ]
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} ,
"graph" : {
"edges" : [
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} ,
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} ,
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} ,
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} ,
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2 W 7 N I 7 X z P g 6 g f u N N T I f z t M C j v Z V D g 8 S M R B 8 n y 8 p s Q / I + d f O n e C r S Z 5 Z k / Z / n M 8 S B 3 H g n y + 9 e T 3 H + 8 l g N D U Q 1 f H I n c c R j + 0 m l K K k 2 T F Y K 0 9 h B a u Q Q k 7 O u 5 E z P k t 0 p 55 O V k Q Q p C j T t S p G l / G x Q z 4 U I V g w 1 w P q U f 2 E G U o f B n M A A t 4 p S n 32 n l + O F a v v d c J 1 / 5 d C U H E Y i e B E x u W s 9 y 4 r Z K D 0 E K / e J H K n l 7 K 8 u d N x n U p m Q p r H 3 D E E F s C 76 B 9 w G E p U W r a I q h r 0 49 d q y C T s M b F 3 N O H r 5 p n g 4 L V D g Q n W 6 n N U g Q f 8 U P x q 79 X m W / E 8 c N P l M b v 3 i l l R M f r O R p C P j 5 D 1 W y D 3 T 3879 i L f j O 7 U d Q + W 1 G O X u l k 4 f v q b B m V M 4 / O E h y a W R r 0 K E H d V K o k h T q a L 5 I 4 S k 0 u W j c J S W K X m M y R I 2 o y Q I S M b q G T Q E r O K O n D / i 3 A 23 T p J t 4 T a e E W 5 b H f 9 N C U 9 A 4 T Y v 5 F 7 a Y o 1 T y w m u t 3 H 97 l B / 8 t l P t n T g G w X e y v H 9 / L Z + 7 M w D 3 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D H I C / 9 k b e A l J g 46 g W M 1 c D Q 0 o a S P o N W I p Q n 7 G k 31 V P x R S y r k e + U p y l S j f Q U / G E I h + w C V q j Z m Z P Q n j R r s k l V t X g u o B U Y T O h P Z B 45 T W y H x / G n R J G p 9 a F Y Z t R Y 5 i a t D Q 4 T 2 c V J T H x 6 S s b I 6 O r V N n d R a x F g E 56 H 7 z D o b s y S x r a m E B p 7 O 0 x b s 2 U S 1 U M h W s D B D o J x k o a a x d 0 t W l i 87 A L x m M u U i l q j x h O e 3 w e f n L U k b 9 i x l 6 H t l R V 9 I w e J B l a 0 H U k d b m o k Z W y H c s I Z C m r r S 36 g g K 947 n U u / 6 y G v Y D w o i S H x T 1 a i l A o 7 T 2 l K 8 a 81 B K u y M K 9 F + F k 5 O c X C B p a F r u O X 1 T 5 x b K X e I E a L g t g w Q a D R 2 M p K m r U O 3 u d h s k c / 8 H q 5 B g a 0 W M 8 U x K q g C G 5 c q R v V N q 9 x Z 8 l h c i Z b 7 R n c y I r Z y 0 z N 6 M m G w Q o r j Q m V 5 V v h z J W U m T W O J 97 P s X R D g 0 8 P e P z T 2 V q m g B g Z J C E y M 73 v B b e A 5 u 8 m f P Q q n y w x x M G o w d J X U C j B E k 1 t x Q + z A 8 K z b S 0 B I y 0 O q G 2 v u 5 O I t 2 v s 8 F Y 2 m 2 I Z G z g u u t K 0 I g t e Z e 8 A 1 w x m X O f y y A L U D j R 0 5 l J E 8 g T s r 4 i m s B q 6 x T J V a 51 Y K 3 C t D + 1 W S e + T R u s q a n S N t W G b T D L 29 g q 1 T M g 2 X v S r 0 F 4 I K a S y 5 U C + l f l C t F q Z j F V 6 p 15 S W n l I j T C 7 J M a n 2 W B C L W / A G m 9 d t i K c 3 E v a L O 3 B F Z i c G S b 5 n R i l X / Q b 1 r P W f b D E 0 D o W T A n U q R u r L c j t T L 1 z M k u V J p l 17 u x g j a c q 4 j n Z 7 i 5 W e G P D 0 u n g N e 32 x I J O D 0 d m X L C S L y g 1 n t + M y i R U E d M I p g I k T 0 K i D 4 e k c A p B K Z H U D q B 5 T m N 1 M A O Q p 10e5 o M m a F r G e u O r r o O T Q N Y 0 I K U o u 6 / s V g p v M J V I p p H o P L U 1 T n o A b / n A 9 E y u 6 E m t L s y 4 q / U t o N F n z q + s J N p H m p Q E k G Z v s r H M Q t + w Y D v x A 6 y l 1 S B h U x m Z K J W W d k u + S m 47 f L B U h a S h N M p N K 2 c F 1 q 1 T B J k d U K v i 14 v 3 W Z h X d g E 9 A t 8 h 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