examples,strings: add a new strings.lorem module; use it in the Markov chain text generator example (#26387)

Author: mike-ward

examples/lorem.v

@@ -2,23 +2,8 @@
 Random Markov Text Generator
 
 This program generates pseudo-random text using a Markov chain built from
-one of several embedded corpora. It produces structured output in the
-form of paragraphs and sentences, with configurable parameters for:
-
-- Markov order (n-gram size)
-- Words per sentence
-- Sentences per paragraph
-- Paragraph count
-- Optional seed phrases and RNG seed
-- Optional corpus selection
-
-Features:
-
-- Five built-in seed phrases, randomly chosen if no seed is provided
-- Paragraphs and sentences with ±20% variability in lengths
-- Automatic reseeding from corpus if seed phrases do not exist in the model
-- Fully self-contained; no external corpus files required
-- Can be run with no parameters and produces readable, multi-paragraph text
+one of several embedded corpora in the strings module. It produces structured output in the
+form of paragraphs and sentences, with configurable parameters.
 
 Usage:
 
@@ -29,72 +14,11 @@ Example:
 
     ./lorem -order 2 -words 12 -sentences 4 -paragraphs 3 -corpus poe
 */
-import rand
+import strings.lorem
 import flag
 import os
-
-// ---------------- Embedded Corpora ----------------
-
-const corpora = {
-	'lorem':  lorem_corpus
-	'poe':    poe_corpus
-	'darwin': darwin_corpus
-	'bard':   shakespeare_corpus
-}
-
-const lorem_corpus = '
-lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor
-incididunt ut labore et dolore magna aliqua Ut enim ad minim veniam quis
-nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat
-Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore
-eu fugiat nulla pariatur Excepteur sint occaecat cupidatat non proident sunt
-in culpa qui officia deserunt mollit anim id est laborum
-'
-
-const poe_corpus = '
-once upon a midnight dreary while I pondered weak and weary
-over many a quaint and curious volume of forgotten lore
-while I nodded nearly napping suddenly there came a tapping
-as of someone gently rapping at my chamber door
-'
-
-const darwin_corpus = '
-when we look to the individuals of the same variety or sub variety of our
-older cultivated plants and animals one of the first points which strikes
-us is that they generally differ much more from each other than do the
-individuals of any one species or variety in a state of nature
-'
-
-const shakespeare_corpus = '
-to be or not to be that is the question
-all the worlds a stage and all the men and women merely players
-the lady doth protest too much methinks
-a rose by any other name would smell as sweet
-et tu brute
-if music be the food of love play on
-now is the winter of our discontent
-we are such stuff as dreams are made on
-brevity is the soul of wit
-some are born great some achieve greatness and some have greatness thrust upon them
-cry havoc and let slip the dogs of war
-all that glisters is not gold
-the fault dear brutus is not in our stars but in ourselves
-to thine own self be true
-lord what fools these mortals be
-shall i compare thee to a summers day
-'
-
-// ---------------- Seed Phrases ----------------
-
-const seed_phrases = [
-	'in the beginning',
-	'once upon a time',
-	'it was the first',
-	'when we consider',
-	'there was a moment',
-]
-
-// ---------------- Main ----------------
+import rand
+import time
 
 fn main() {
 	mut fp := flag.new_flag_parser(os.args[1..])
@@ -106,17 +30,23 @@ fn main() {
 	words_per_sentence := fp.int('words', `w`, 10, 'Words per sentence [default: 10]')
 	sentences_per_paragraph := fp.int('sentences', `s`, 5, 'Sentences per paragraph [default: 5]')
 	paragraphs := fp.int('paragraphs', `p`, 3, 'Paragraph count [default: 3]')
-	corpus_name := fp.string('corpus', `c`, 'lorem', 'Corpus name (lorem, poe, darwin, bard) [default: lorem')
+	corpus_name := fp.string('corpus', `c`, 'lorem', 'Corpus name (lorem, poe, darwin, bard) [default: lorem]')
 	seed_text := fp.string('seed', `S`, '', 'Seed phrase (random if omitted)')
-	rng_seed := fp.int('rngseed', `r`, 0, 'RNG seed (0 = non-deterministic)')
+	mut rng_seed := fp.int('rngseed', `r`, 0, 'RNG seed (0 = random)')
 
 	fp.finalize() or {
 		eprintln(err)
 		return
 	}
 
-	text := generate_text(
-		order:                   order
+	if rng_seed == 0 {
+		t := time.now().unix_milli()
+		rand.seed([u32(t), u32(t >> 32)])
+		rng_seed = rand.int()
+	}
+
+	text := lorem.generate(
+		markov_order:            order
 		words_per_sentence:      words_per_sentence
 		sentences_per_paragraph: sentences_per_paragraph
 		paragraphs:              paragraphs
@@ -127,127 +57,3 @@ fn main() {
 
 	println(text)
 }
-
-struct LoremCfg {
-	order                   int = 2
-	words_per_sentence      int = 10
-	sentences_per_paragraph int = 5
-	paragraphs              int = 3
-	corpus_name             string
-	seed_text               string
-	rng_seed                int
-}
-
-// ---------------- Text Generation ----------------
-
-fn generate_text(cfg LoremCfg) string {
-	if cfg.rng_seed != 0 {
-		rand.seed([u32(cfg.rng_seed)])
-	}
-
-	seed := match cfg.seed_text != '' {
-		true { cfg.seed_text }
-		else { random_seed_phrase() }
-	}
-
-	corpus := select_corpus(cfg.corpus_name)
-	tokens := tokenize(corpus)
-
-	if tokens.len <= cfg.order {
-		eprintln('corpus too small for selected order')
-		return ''
-	}
-
-	model := build_markov(tokens, cfg.order)
-
-	mut state := tokenize(seed)
-	if state.len < cfg.order {
-		start := rand.intn(tokens.len - cfg.order) or { 0 }
-		state = tokens[start..start + cfg.order].clone()
-	}
-
-	mut out := []string{}
-
-	for pi in 0 .. cfg.paragraphs {
-		if pi != 0 {
-			out << '\n\n'
-		}
-		sentences := vary(cfg.sentences_per_paragraph, 1)
-
-		for si in 0 .. sentences {
-			if si != 0 {
-				out << ' '
-			}
-			words := vary(cfg.words_per_sentence, 3)
-			mut sentence := []string{}
-
-			for _ in 0 .. words {
-				key := state.join('\u0001')
-				nexts := model[key] or {
-					start := rand.intn(tokens.len - cfg.order) or { 0 }
-					state = tokens[start..start + cfg.order].clone()
-					continue
-				}
-
-				next := nexts[rand.intn(nexts.len) or { 0 }]
-				sentence << next
-
-				state = state[1..].clone()
-				state << next
-			}
-
-			if sentence.len > 0 {
-				out << sentence.join(' ').capitalize()
-				out << '.'
-			}
-		}
-	}
-
-	return out.join('')
-}
-
-// ---------------- Utilities ----------------
-
-fn vary(base int, min int) int {
-	delta := int(f32(base) * 0.2)
-	if delta == 0 {
-		return base
-	}
-	offset := rand.intn(delta * 2 + 1) or { 0 } - delta
-	val := base + offset
-	return if val < min { min } else { val }
-}
-
-fn select_corpus(name string) string {
-	if name != '' {
-		if corpus := corpora[name] {
-			return corpus
-		}
-		eprintln('unknown corpus: ${name}')
-		exit(1)
-	}
-
-	keys := corpora.keys()
-	key := keys[rand.intn(keys.len) or { 0 }]
-	return corpora[key]
-}
-
-fn random_seed_phrase() string {
-	return seed_phrases[rand.intn(seed_phrases.len) or { 0 }]
-}
-
-fn tokenize(text string) []string {
-	return text
-		.replace_each(['\n', ' ', '\t', ' '])
-		.split(' ')
-		.filter(it.len > 0)
-}
-
-fn build_markov(tokens []string, order int) map[string][]string {
-	mut model := map[string][]string{}
-	for i in 0 .. tokens.len - order {
-		key := tokens[i..i + order].join('\u0001')
-		model[key] << tokens[i + order]
-	}
-	return model
-}