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`cj/markov-join-tokens' collects tokens in a list and `mapconcat's once instead of repeated string concatenation. `cj/markov-generate' uses `push'/`nreverse' instead of repeated `append'. The Markov keys are cached as a vector so random key selection is O(1). Re-enabled the benchmark tests (the `:slow' tags were stale) and added a `cj/lipsum-title' test after byte-compilation flagged a malformed form there. `assets/liber-primus.txt' is left as-is (36 KB / 5,374 words, small enough not to need trimming). 100K-word learning now measures about 196 ms.
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This reverts commit 94d4e6c9624046cef20236a8073a4857d3bd7827.
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Rename `lorem-generator.el` to `lorem-optimum.el` for fun.
Enhance text tokenization, Markov chain learning, and text
generation functions. Introduce new configuration variables for
training files and improve efficiency with vectorized access. Add
comprehensive benchmarks and unit tests under `tests/`. This
improves performance and lays groundwork for further extensions.
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