I haven’t found doc on how to use tfjs.converters directly, but I was able to go beyond the tensorflow_text with the following code (based on the logic of the CLI converter):
import tensorflow as tf
import tensorflowjs as tfjs
import tensorflow_hub as hub
import tensorflow_text

from tensorflowjs.converters import tf_saved_model_conversion_v2

tf_saved_model_conversion_v2.convert_tf_hub_module(
    "https://tfhub.dev/google/universal-sentence-encoder-multilingual/3",
    "web_model",
    signature="serving_default"
)

However, I now get the following error:
ValueError: Unsupported Ops in the model before optimization
SentencepieceOp, SegmentSum, RaggedTensorToSparse, ParallelDynamicStitch, SentencepieceTokenizeOp, DynamicPartition

It seems that this multilingual model uses different operators than the universal sentence encoder provided of TF.js model’s page.