hey how can i use `Hyde Query Transform`

from llama_index.core.chat_engine import CondensePlusContextChatEngine

condense_prompt = """
  Given the following conversation between a user and an AI assistant and a follow up question from user,
  please write a passage to answer the question
  Try to include as many key details as possible.

  Chat History:
  {chat_history}
  Follow Up Input: {question}
  Passage:"""

chat_engine = CondensePlusContextChatEngine.from_defaults(retriever, llm=llm, condense_prompt=condense_prompt)

agent_prompt = """

For each user input, you will:

1. Generate two search queries:
   - The first query will be the original user input, unmodified.
   - The second query will be a rephrased or expanded version of the original, aimed at capturing additional relevant information.

2. Use both queries to gather information and formulate your response.

3. Provide a comprehensive answer based on the combined results of both queries.

Remember to tailor your responses to the context of mortgage business and loan application management.

Input: {query}
Please process the input according to the steps above and provide your response.
"""

query_engine_tools = [
    QueryEngineTool(
        query_engine=mloflo_engine,
        metadata=ToolMetadata(
            name="tool-name",
            description=(
                "Provides information about ..., Use this to address user queries"
                "Use a detailed plain text question as input to the tool."
            ),
        ),
    )
]

from llama_index.agent.openai import OpenAIAgent
agent = OpenAIAgent.from_tools(query_engine_tools, verbose=True, system_propmt=agent_prompt)