Skip to main content

​
embedding

Function
This function is defined in the embed module.
Generate embeddings for text using LiteLLM. This is the primary embedding function that supports all LiteLLM embedding providers (OpenAI, Azure, Cohere, Voyage, etc.).

​
Signature

def embedding(input: Union[str, List[str]], model: str, dimensions: Optional[int], encoding_format: str, timeout: float, api_key: Optional[str], api_base: Optional[str], metadata: Optional[Dict[str, Any]]) -> EmbeddingResult

​
Parameters

​
input
Union
required
Text or list of texts to embed
​
model
str
default:"'text-embedding-3-small'"
Model name (e.g., “text-embedding-3-small”, “text-embedding-3-large”)
​
dimensions
Optional
Optional output dimensions (for models that support it)
​
encoding_format
str
default:"'float'"
“float” or “base64”
​
timeout
float
default:"600.0"
Request timeout in seconds
​
api_key
Optional
Optional API key override
​
api_base
Optional
Optional API base URL override
​
metadata
Optional
Optional metadata for tracing **kwargs: Additional arguments passed to litellm.embedding()

​
Returns

​
Returns
EmbeddingResult
EmbeddingResult with embeddings list, model, usage, and metadata

​
Usage

>>> from praisonaiagents import embedding
    >>> result = embedding("Hello, world!")
    >>> print(len(result.embeddings[0]))
    1536

    >>> result = embedding(["Hello", "World"], model="text-embedding-3-large")
    >>> print(len(result.embeddings))
    2