code: def test_langchainTransform(self):
      # construct langchain transformer using the chain defined above. And test if the generated
      # column has the expected result.
      dataframes_to_test = spark.createDataFrame(
          [(0, "docker"), (0, "spark"), (1, "python")],
          ["label", "technology"],
      )
      self._assert_chain_output(
          self.langchainTransformer, dataframes_to_test
      )
  
file_path: SynapseML/cognitive/src/test/python/synapsemltest/services/langchain/test_LangchainTransform.py
imports: import os, json, subprocess, unittest
  from langchain.chains import LLMChain
  from langchain.prompts import PromptTemplate
  from langchain.llms import AzureOpenAI
  from synapse.ml.services.langchain import LangchainTransformer
  from synapsemltest.spark import *
label_desc: Use image node_id 5 for calling the LangchainTransformTest obj's underlying member method code with example usage: obj.test_langchainTransform() without return types