Embed and Add to Knowledge Base

Generate document embeddings and write them to a knowledge base index for retrieval.

This node saves vectors to the knowledge base. Use Text Embedding if you only need vectors for further processing.

Configure the knowledge base

Bind documents from parsing or chunking and select the target knowledge base.

Setting

Description

Knowledge base

Required; select or create a target that provides the index table and embedding model settings

Multi-level retrieval

Enabled by default; builds document, section, and chunk indexes

Chunks per section

Default: 3; groups consecutive chunks into sections when multi-level retrieval is enabled

The selected knowledge base supplies table_name and embedding_model. Retain document source metadata for index management and tracing.

Use the output

Output

Purpose

written

Number of document or index rows actually written

table_name

Table receiving the index

embedding_model

Model used to build the index

With multi-level retrieval, written includes rows at document, section, and chunk levels.

Example: index manuals

Flow: Read MOI Volume → General Document Parsing → Segment → Embed and Add to Knowledge Base.

Select the manual knowledge base, keep multi-level retrieval enabled, and set chunks per section to 3. After running, check the target table and row count, then verify the content through knowledge base retrieval.

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