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AI/ML API

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Embedding Generation

AI-generated

Overview

This node operation generates numeric vector embeddings from input text using a specified AI/ML model. It is useful for transforming text data into a format suitable for machine learning, semantic search, or similarity comparisons. For example, it can convert product descriptions into embeddings for recommendation systems or analyze customer feedback by embedding sentences.

Use Case Examples

  1. Generating embeddings for text documents to enable semantic search.
  2. Converting user input into embeddings for chatbot understanding.
  3. Creating vector representations of sentences for clustering or classification tasks.

Properties

Name Meaning
Model Name or ID Select the AI/ML model to use for generating embeddings.
Input Text The text string that will be converted into a numeric embedding vector.
Extract From Response Determines which part of the embedding response to return: the first embedding vector, all embedding vectors, or the full raw JSON response.
Embedding Options Additional optional parameters to fine-tune the embedding request, such as encoding format and user identifier.

Output

JSON

  • embedding - The extracted embedding vector(s) or raw JSON response depending on the extraction option selected.

Dependencies

  • Requires an API key credential for the AI/ML API service to authenticate requests.

Troubleshooting

  • Common errors include unsupported operation errors if the operation parameter is incorrect.
  • API request failures due to invalid model IDs or network issues.
  • Handling errors gracefully with continueOnFail option to avoid stopping the workflow on single item failure.

Discussion