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embedAll
Last update:
May 18, 2026
Description
Generates embeddings for multiple text inputs in a single call. This method is optimized for throughput and is the recommended way to embed:
- document batches during ingestion, or
- large sets of knowledge‑base entries.
Syntax
embedAll(array text)Returns
A struct containing:
- embeddings – an array of vectors (one per input string, in the same order).
- tokenUsage – aggregated token usage metrics (if provider makes it available).
- finishReason – reason the call completed (if provided by the provider).
- metadata – provider‑specific metadata.
Parameters
Parameters
Parameter | Type | Required | Description |
text | Array | Yes | Array of text strings to embed (batch input). |
Usage
Use embedAll() whenever you have more than one string to embed.
Example
<cfscript>
embeddingModel = {
provider: "openai",
modelName: "text-embedding-3-small",
apiKey: #application.apiKey#
};
texts = [
"Machine learning is a subset of artificial intelligence",
"ColdFusion is a rapid application development platform",
"Vector databases enable semantic search capabilities",
"Embeddings represent text as numerical vectors",
"Natural language processing uses neural networks"
];
result = embeddingModel.embedAll(texts);
writeDump(result)
break;
hasEmbeddings = isDefined("result") AND isStruct(result) AND structKeyExists(result, "embeddings") AND isArray(result.embeddings) AND arrayLen(result.embeddings) EQ 5;
writeOutput(hasEmbeddings);
</cfscript>
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