code: def test_causalLM_embeddings(self):
      bigdl_embeddings = BloomEmbeddings(
          model_path=self.bloom_model_path,
          model_kwargs={"trust_remote_code": True},
          native=False,
      )
      text = "This is a test document."
      query_result = bigdl_embeddings.embed_query(text)
      doc_result = bigdl_embeddings.embed_documents([text])
  
      bigdl_llm = BloomLLM(
          model_path=self.bloom_model_path,
          model_kwargs={"trust_remote_code": True},
          native=False,
      )
      res = bigdl_llm(text)
  
file_path: BigDL/python/llm/test/langchain/test_transformers_api.py
imports: from bigdl.llm.langchain.llms import TransformersLLM, TransformersPipelineLLM, LlamaLLM, BloomLLM
  from bigdl.llm.langchain.embeddings import TransformersEmbeddings, LlamaEmbeddings, BloomEmbeddings
  from langchain.document_loaders import WebBaseLoader
  from langchain.indexes import VectorstoreIndexCreator
  from langchain.chains.question_answering import load_qa_chain
  from langchain.chains.chat_vector_db.prompts import CONDENSE_QUESTION_PROMPT, QA_PROMPT
  from langchain.text_splitter import CharacterTextSplitter
  from langchain.vectorstores import Chroma
  import pytest
  from unittest import TestCase
  import os
label_desc: Use image node_id 3 for calling the Test_Langchain_Transformers_API obj's underlying member method code with example usage: obj.test_causalLM_embeddings() without return types