Error querying SageMaker endpoint

[lshang0311]

Link to the notebook Retrieval-Augmented Generation: Question Answering based on Custom Dataset with Open-sourced [LangChain](https://python.langchain.com/en/latest/index.html) Library

Describe the bug Query the endpoint

payload = {
    "text_inputs": question,
    "max_length": 100,
    "num_return_sequences": 1,
    "top_k": 50,
    "top_p": 0.95,
    "do_sample": True,
}

list_of_LLMs = list(_MODEL_CONFIG_.keys())
list_of_LLMs.remove("huggingface-textembedding-gpt-j-6b")  # remove the embedding model

for model_id in list_of_LLMs:
    endpoint_name = _MODEL_CONFIG_[model_id]["endpoint_name"]
    query_response = query_endpoint_with_json_payload(
        json.dumps(payload).encode("utf-8"), endpoint_name=endpoint_name
    )
    generated_texts = _MODEL_CONFIG_[model_id]["parse_function"](query_response)
    print(f"For model: {model_id}, the generated output is: {generated_texts[0]}\n")

Gives the following error:

ModelError: An error occurred (ModelError) when calling the InvokeEndpoint operation: Received client error (400) from primary with message "{
  "code": 400,
  "type": "InternalServerException",
  "message": "model_fn() takes 1 positional argument but 2 were given"
}

To reproduce Dependencies: !pip install sagemaker==2.181 !pip install ipywidgets==7.0.0 --quiet !pip install langchain==0.0.148 --quiet !pip install faiss-cpu --quiet

Logs

[lshang0311]

Screenshot of the error: