1  from __future__ import annotations
 2  
 3  """HuggingFace embedding model implementation."""
 4  
 5  from typing import Any
 6  
 7  from langchain_huggingface import HuggingFaceEmbeddings
 8  
 9  from .constants import DEFAULT_HUGGINGFACE_MODEL
10  from .protocol import Embeddings
11  
12  
13  def create_huggingface_embedding(config: dict[str, Any]) -> Embeddings:
14      """Create HuggingFace embedding model.
15  
16      Parameters
17      ----------
18      config
19          Configuration dictionary. Common parameters include:
20          - model_name: str (optional) - Model name (defaults to DEFAULT_HUGGINGFACE_MODEL)
21          - model_kwargs: dict (optional) - Additional model arguments
22          - encode_kwargs: dict (optional) - Additional encoding arguments
23          - Other parameters supported by HuggingFaceEmbeddings constructor.
24          Invalid parameters will be caught by HuggingFaceEmbeddings and raise clear errors.
25  
26      Returns
27      -------
28      Embeddings instance.
29  
30      Raises
31      ------
32      ValueError
33          If model creation fails or invalid parameters are provided.
34      """
35  
36      if "model_name" not in config:
37          config = {**config, "model_name": DEFAULT_HUGGINGFACE_MODEL}
38  
39      try:
40          return HuggingFaceEmbeddings(**config)
41      except TypeError as e:
42          raise ValueError(
43              f"Invalid parameter for HuggingFace embedding model: {e}. "
44              "Check HuggingFaceEmbeddings documentation for valid parameters."
45          ) from e
46      except Exception as e:
47          raise ValueError(f"Failed to create HuggingFace embedding model: {e}") from e