class_docstr: A component for computing Document embeddings using OpenAI models.
  The embedding of each Document is stored in the `embedding` field of the Document.
  
  Usage example:
  ```python
  from haystack import Document
  from haystack.components.embedders import AzureOpenAIDocumentEmbedder
  
  doc = Document(content="I love pizza!")
  
  document_embedder = AzureOpenAIDocumentEmbedder()
  
  result = document_embedder.run([doc])
  print(result['documents'][0].embedding)
  
  # [0.017020374536514282, -0.023255806416273117, ...]
  ```
docstr: Data that is sent to Posthog for usage analytics.
code: def _get_telemetry_data(self) -> Dict[str, Any]:
      """
      Data that is sent to Posthog for usage analytics.
      """
      return {"model": self.azure_deployment}
  
file_path: haystack/haystack/components/embedders/azure_document_embedder.py
imports: import os
  from typing import List, Optional, Dict, Any, Tuple
  from openai.lib.azure import AzureADTokenProvider, AzureOpenAI
  from tqdm import tqdm
  from haystack import component, Document, default_to_dict
label_desc: Use image node_id 2 for calling the AzureOpenAIDocumentEmbedder obj's underlying member method code with example usage: obj._get_telemetry_data() and returns: dict