Document Text Embedding¶
Extract text records from a document visual manifest, generate vectors, and write them to a text index table.
Use it alongside image indexing in multimodal flows. For ordinary document arrays going directly to a knowledge base, use Embed and Add to Knowledge Base.
Bind the manifest and text index¶
Check template-provided bindings, or supply these inputs when building a flow yourself.
Input |
Description |
|---|---|
Visual manifest |
Upstream manifest object or manifest file reference |
|
Required target table for text vectors |
|
Required text embedding model |
|
When false, skips writes and returns |
Multi-level indexing is off by default. Enable it if needed.
Bind a manifest containing both text and source information.
Use the output¶
documents contains text records built from the manifest, and documents_count counts them. written counts vector rows actually written. Check text_vector_table and embedding_model against the intended configuration.
Use status to distinguish writes from a disabled node.
Example: add text retrieval¶
Flow: Build Document Visual Manifest → Document Text Embedding.
Bind the manifest and specify the text table and embedding model. Connect Image Embedding separately for visual retrieval, then check the write results of both indexes.