code: def test_rag_pipeline_embedder_exist_if_model_is_given():
      rag_pipe = build_rag_pipeline(
          document_store=InMemoryDocumentStore(),
          embedding_model="sentence-transformers/all-mpnet-base-v2",
      )
      assert "text_embedder" in rag_pipe.pipeline.graph.nodes
  
file_path: haystack/test/pipelines/test_rag_pipelines.py
imports: import os
  import pytest
  from haystack.dataclasses import Answer
  from haystack.document_stores.in_memory import InMemoryDocumentStore
  from haystack.pipeline_utils.rag import build_rag_pipeline
  from haystack.testing.factory import document_store_class
label_desc: Use image node_id 3 for calling a global function with example usage: test_rag_pipeline_embedder_exist_if_model_is_given() without return types