code: def query(question):
      context_docs = cursor.query(
          f"""
          SELECT data
          FROM embedding_table
          ORDER BY Similarity(embedding('{question}'), features)
          LIMIT 5;
      """
      ).df()
  
      # Merge all context information.
      context = "\n".join(context_docs["embedding_table.data"])
  
      # run llm
      llm = GPT4All("ggml-model-gpt4all-falcon-q4_0.bin")
      llm.set_thread_count(16)
  
      message = f"""If the context is not relevant, please answer the question by using your own knowledge about the topic.
      
      {context}
      
      Question : {question}"""
  
      answer = llm.generate(message)
  
      print("\n> Answer:", answer)
  
label_desc: Use image node_id 1 for calling a global function with example usage: query(question) without return types