`UnboundLocalError local variable

...
...
    query_wrapper_prompt = "[INST] {query_str} [/INST]"
    embed_model='local:BAAI/bge-base-en'

    server_url = os.getenv('TGIS_SERVER_URL', 'http://localhost') # Get server url from env else default
    server_port = os.getenv('TGIS_SERVER_PORT', '8049') # Get server port from env else default

    inference_server_url=f"{server_url}:{server_port}/"


    tgis_predictor = LangChainLLM(
        llm=HuggingFaceTextGenInference(
            inference_server_url=inference_server_url,
            max_new_tokens=256,
            temperature=temperature,
            repetition_penalty=repetition_penalty,
            server_kwargs={},
        ),
    )

    service_context = ServiceContext.from_defaults(chunk_size=1024, llm=tgis_predictor, 
                                                   embed_model=embed_model,
                                                   query_wrapper_prompt=query_wrapper_prompt)

from llama_index.prompts import Prompt

query_wrapper_prompt = Prompt("...")

    query_wrapper_prompt = Prompt("[INST] {query_str} [/INST]")
...
    service_context = ServiceContext.from_defaults(chunk_size=1024, llm=tgis_predictor, 
                                                   query_wrapper_prompt=query_wrapper_prompt,
#                                                   system_prompt=system_prompt,
                                                   embed_model=embed_model)

UnboundLocalError: local variable 'default_template' referenced before assignment

    service_context = ServiceContext.from_defaults(chunk_size=1024, llm=tgis_predictor, 
                                                   query_wrapper_prompt=query_wrapper_prompt,
                                                   system_prompt=system_prompt,
                                                   embed_model=embed_model)

    service_context = ServiceContext.from_defaults(chunk_size=1024, llm=tgis_predictor, 
                                                   query_wrapper_prompt=query_wrapper_prompt,
                                                   embed_model=embed_model)