create_embeddings
Generate vector embeddings from files in a storage bucket to enable semantic search and AI applications. Specify chunking parameters and embedding models for document processing.
Instructions
Embed a bucket that containe files.
Args:
bucket_name: Required. Bucket Name. The bucket must exist (string)
document_chunk_size: Optional. Document Chunk Size (integer)
document_chunk_overlap_size: Optional. Document Chunk Overlap Size (integer)
embedding_model: Optional. Supported models (thenlper/gte-large,
intfloat/multilingual-e5-large, sentence-transformers/all-mpnet-base-v2)
to vectorize and embed documents.
loader: Optional. (default, intercom) (string)
Agent should prefer only rely on required fields unless user explicitly
provides values for optional fields.
Returns:
Dict[str, Any]: Response data containing the embeddingsInput Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| request | Yes |