节点与集成
Embeddings Azure OpenAI
Use the Embeddings Azure OpenAI node to generate embeddings1 for a given text.
On this page, you'll find the node parameters for the Embeddings Azure OpenAI node, and links to more resources.
Node options
- Model (Deployment) Name: Select the model (deployment) to use for generating embeddings.
- Batch Size: Enter the maximum number of documents to send in each request.
- Strip New Lines: Select whether to remove new line characters from input text (turned on) or not (turned off). n8n enables this by default.
- Timeout: Enter the maximum amount of time a request can take in seconds. Set to
-1for no timeout.
Templates and examples
Browse Embeddings Azure OpenAI node documentation integration templates or search all templates
Related resources
Refer to LangChains's OpenAI embeddings documentation for more information about the service.
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
本页来自 N8N 英文官方网站固定快照，并转换成 xueai 静态页面。内容以 N8N 持续更新的官方页面为准。