code: def test_run(self, mock_check_valid_model):
      docs = [
          Document(content="I love cheese", meta={"topic": "Cuisine"}),
          Document(
              content="A transformer is a deep learning architecture",
              meta={"topic": "ML"},
          ),
      ]
  
      with patch(
          "huggingface_hub.InferenceClient.feature_extraction"
      ) as mock_embedding_patch:
          mock_embedding_patch.side_effect = mock_embedding_generation
  
          embedder = HuggingFaceTEIDocumentEmbedder(
              model="BAAI/bge-small-en-v1.5",
              token="fake-api-token",
              prefix="prefix ",
              suffix=" suffix",
              meta_fields_to_embed=["topic"],
              embedding_separator=" | ",
          )
  
          result = embedder.run(documents=docs)
  
          mock_embedding_patch.assert_called_once_with(
              text=[
                  "prefix Cuisine | I love cheese suffix",
                  "prefix ML | A transformer is a deep learning architecture suffix",
              ]
          )
      documents_with_embeddings = result["documents"]
  
      assert isinstance(documents_with_embeddings, list)
      assert len(documents_with_embeddings) == len(docs)
      for doc in documents_with_embeddings:
          assert isinstance(doc, Document)
          assert isinstance(doc.embedding, list)
          assert len(doc.embedding) == 384
          assert all(isinstance(x, float) for x in doc.embedding)
  
imports: from unittest.mock import MagicMock, patch
  import numpy
  import pytest
  from huggingface_hub.utils import RepositoryNotFoundError
  from haystack.components.embedders.hugging_face_tei_document_embedder import HuggingFaceTEIDocumentEmbedder
  from haystack.dataclasses import Document
label_desc: Use image node_id 10 for calling the TestHuggingFaceTEIDocumentEmbedder obj's underlying member method code with example usage: obj.test_run(mock_check_valid_model) without return types