Generate embeddings
Runtime API - Embeddings
Generate embeddings
Generate embeddings for an array of texts.
Authentication:
- Requires
x-api-keyheader with valid API key or internal service key. - Requires
x-runflow-tenant-idheader for tenant identification.
Credential Resolution:
- Credentials are resolved automatically from tenant’s LLM Providers configuration.
- Use ‘providerName’ to specify which provider configuration to use.
Supported Providers:
openai: text-embedding-3-small, text-embedding-3-large, text-embedding-ada-002azure_openai: Azure OpenAI deploymentscohere: embed-english-v3.0, embed-multilingual-v3.0
Example Request:
{
"input": ["Hello, world!", "How are you?"],
"model": "text-embedding-3-small",
"dimensions": 1536
}
POST
Generate embeddings
Documentation Index
Fetch the complete documentation index at: https://docs.runflow.ai/llms.txt
Use this file to discover all available pages before exploring further.
Body
application/json
Array of texts to generate embeddings for
Example:
["Hello, world!", "How are you?"]Embeddings model
Example:
"text-embedding-3-small"
Embeddings provider
Available options:
openai, azure_openai, cohere Provider name (configured in LLM Providers) for credential resolution
Example:
"My OpenAI Production"
Embedding dimensions (only for models that support it)
Example:
1536
Response
Embeddings generated successfully