Sample a string by real-valued scores

You are given: - A list of strings `texts` (e.g., user comments), length `n`. - A list of floating-point scores `scores` of length `n`, where each score can be any real value, including `-∞` or `+∞`. Design an algorithm/function that **randomly returns one string** from `texts` such that the probability of returning `texts[i]` is proportional to the score distribution. Define the sampling rule explicitly as follows: - If all scores are finite, sample index `i` with probability \[ p_i = \frac{e^{scores[i]}}{\sum_{j=0}^{n-1} e^{scores[j]}}\quad\text{(softmax)}. \] - If one or more scores are `+∞`, return one of the `+∞` items uniformly at random. - If all scores are `-∞` (so all weights are zero), return any item uniformly at random. Requirements: - Time complexity: **O(n)** per sample. - Must be numerically stable for large/small scores. - Clearly state how you handle corner cases (empty input, NaN scores if they appear, etc.).