Maximize watched duration under consecutive-sum limit

You have a list of videos in a feed. Video *i* has duration `d[i]` (positive integer). A user has an “attention span” limit `A`. You want to select a **subset of videos to watch** (keeping the original order, i.e., choose a subsequence of indices `i1 < i2 < ... < ik`) to **maximize total watched time**: \[ \text{maximize } \sum_{t=1}^{k} d[i_t] \] subject to the constraint that **any two consecutively watched videos** do not exceed the attention span when added: \[ d[i_t] + d[i_{t+1}] \le A \quad \text{for all } t = 1..k-1 \] ### Task Write an algorithm/function that returns the **maximum total watched duration** achievable. ### Assumptions / clarifications - `n = len(d)` can be large enough that brute-forcing all subsets is too slow. - Watching 0 or 1 video is always allowed. ### Follow-up If the user is allowed to **watch the same video multiple times**, how would you modify the approach? - To avoid an unbounded/infinite answer, assume there is an additional limit `K` = maximum number of videos the user can watch total (including repeats). Return the maximum total watched duration under the same consecutive-sum constraint.