Getting this ERROR Main: - Unable to infer schema for JSON. It must be specified manually

I'm trying to merge my ground truth values with data captured(for Model Quality Monitoring) using sagemaker-model-monitor-groundtruth-merger container image.

def run_merge_job_processor(
        region,
        instance_type,
        role,
        bucket_name,
        groundtruth_path,
        endpoint_input,
        merge_path,
        instance_count=1,
        ):
     
    
    groundtruth_input_1 = ProcessingInput(input_name="groundtruth_input_1",
                              source="s3://{}/{}".format(bucket_name, groundtruth_path),
                              destination=f"/opt/ml/processing/groundtruth{datetime.utcnow():%Y/%m/%d/%H}",
                              s3_data_type="S3Prefix",
                              s3_input_mode="File")
    
    "/".join(endpoint_input.split("/")[3:])
    
    endpoint_input_1 = ProcessingInput(
                          input_name="endpoint_input_1",
                          source="s3://{}/{}".format(bucket_name, endpoint_input),
                          destination="/opt/ml/processing/input_data/{}".format("/".join(endpoint_input.split("/")[3:])),
                          s3_data_type="S3Prefix",
                          s3_input_mode="File")
     
    output = ProcessingOutput(
                          output_name="result",
                          source="/opt/ml/processing/output",
                          destination=f"s3://{bucket_name}/{merge_path}")
    
    
    inputs = [ groundtruth_input_1, endpoint_input_1 ]
    outputs = [ output ]
    
    env = {
        "dataset_format": "{\"sagemakerCaptureJson\": {\"captureIndexNames\": [\"endpointInput\",\"endpointOutput\"]}}",
        'dataset_source': '/opt/ml/processing/input_data',
        'ground_truth_source': '/opt/ml/processing/groundtruth',
        'output_path': '/opt/ml/processing/output'
    }
    
    processor = Processor(image_uri=get_model_monitor_container_uri(region),
                          instance_count=instance_count,
                          instance_type=instance_type,
                          role=role,
                          env=env,
                          )
    
    return processor.run(
        inputs=inputs,
        outputs=outputs,
        wait=True

The above code that I've used for creating the processing job where my processing job is getting failed with the following error.