code: def test_run(self):
      docs = [
          Document(content="I love cheese", meta={"topic": "Cuisine"}),
          Document(
              content="A transformer is a deep learning architecture",
              meta={"topic": "ML"},
          ),
      ]
      # the default model is text-embedding-ada-002 even if we don't specify it, but let's be explicit
      embedder = AzureOpenAIDocumentEmbedder(
          azure_deployment="text-embedding-ada-002",
          meta_fields_to_embed=["topic"],
          embedding_separator=" | ",
          organization="HaystackCI",
      )
  
      result = embedder.run(documents=docs)
      documents_with_embeddings = result["documents"]
      metadata = result["meta"]
  
      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) == 1536
          assert all(isinstance(x, float) for x in doc.embedding)
      assert metadata == {
          "model": "ada",
          "usage": {"prompt_tokens": 15, "total_tokens": 15},
      }
  
imports: import os
  import pytest
  from haystack import Document
  from haystack.components.embedders import AzureOpenAIDocumentEmbedder
label_desc: Use image node_id 3 for calling the TestAzureOpenAIDocumentEmbedder obj's underlying member method code with example usage: obj.test_run() without return types