v44

latestOpenAPI 3.1.0Proprietaryraw.githubusercontent.com2026-05-192301780.0 KB

LLMs

Create embeddings

Create vector embeddings from text using OpenAI-compatible models. Perfect for semantic search, document similarity, and building RAG systems for legal documents.

post/llm/v1/embeddings

Request body

modelstring required

Embedding model to use (e.g., text-embedding-ada-002, text-embedding-3-small)

encoding_format'float' | 'base64'

Format for returned embeddings

dimensionsinteger

Number of dimensions for the embeddings (model-specific)

userstring

Unique identifier for the end-user

Response

Embeddings created successfully

objectstring

modelstring

Example response

{
  "object": "list",
  "data": [
    {
      "object": "embedding"
    }
  ]
}