Type: nodetool.text.Embedding

Namespace: nodetool.text

Description

Generate vector representations of text using any supported embedding provider (OpenAI, Gemini, Mistral). embeddings, similarity, search, clustering, classification, vectors, semantic

Use cases:
- Semantic search and recommendation
- Text clustering and classification
- Anomaly detection
- Measuring text similarity and diversity

Properties

Property Type Description Default
model embedding_model The embedding model to use {"type":"embedding_model","provider":"openai","...
input str The text to embed ``
chunk_size int Size of text chunks for embedding (used when input exceeds model limits) 4096

Outputs

Output Type Description
output list  

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