节点与集成
Embeddings Oracle Database
Use the Embeddings Oracle Database node to generate embeddings1 with ONNX models stored in Oracle Database. This node is useful for workflows that perform semantic search, similarity matching, retrieval-augmented generation, or other tasks that require vector representations of text.
On this page, you'll find the node parameters for the Embeddings Oracle Database node, and links to more resources.
Node parameters
- Model: Select the ONNX model used to generate embeddings. Choose a model from the list of models available in your Oracle Database instance or specify a model ID manually. The selected model determines the embedding dimensions and supported input types.
The node loads available models from the USER_MINING_MODELS view in the configured Oracle Database connection. Only models accessible to the current database user are displayed.
Templates and examples
Browse Embeddings Oracle Database node documentation integration templates or search all templates
Related resources
Refer to Oracle's ONNX model import documentation for more information about importing ONNX models into Oracle Database.
View n8n's Advanced AI documentation.
Footnotes
- Back
Embeddings are numerical representations of data using vectors. They're used by AI to interpret complex data and relationships by mapping values across many dimensions. Vector databases, or vector stores, are databases designed to store and access embeddings.
官方原文和授权
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