Text processing
Slugs, case conversion, diffs, regex, keywords, token estimates, edit distance, readability, PII redaction.
Slugify
POST /api/slugifyTurn any text into a URL-safe slug (lowercase, hyphenated, diacritics stripped).
try in playground →Case convert
POST /api/caseConvert text between camelCase, PascalCase, snake_case, kebab-case, CONSTANT_CASE, Title Case, lowercase and UPPERCASE.
try in playground →Text statistics
POST /api/text-statsCounts for any text in one call: characters (Unicode code points), words, sentences, paragraphs, avgWordLength.
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POST /api/keywordsTop keywords and two-word phrases by frequency (stopwords removed).
try in playground →Text diff
POST /api/text-diffLine-by-line diff of two texts (LCS).
try in playground →Regex test
POST /api/regexRun a regular expression against text.
try in playground →Lorem ipsum
GET /api/loremPlaceholder text. ?paragraphs=1..20 or ?words=1..2000.
try in playground →Count
POST /api/countCount characters, words, lines, and (optionally) occurrences of a substring in text.
try in playground →Truncate
POST /api/truncateTruncate text to a maximum length, adding an ellipsis (or custom suffix).
try in playground →Sort lines
POST /api/sort-linesSort the lines of a text. order: asc (default) | desc | numeric.
try in playground →Dedupe lines
POST /api/dedupe-linesRemove duplicate lines, preserving first-seen order.
try in playground →Edit distance
POST /api/levenshteinLevenshtein edit distance between two strings, plus a 0-1 similarity ratio.
try in playground →Redact PII
POST /api/redactMask emails, phone numbers, credit-card-like numbers, IPs, and SSNs in text.
try in playground →Extract entities
POST /api/extract-entitiesPull emails, URLs, IPv4s, @mentions, and #hashtags out of free text.
try in playground →Readability
POST /api/readabilityFlesch Reading Ease score and Flesch–Kincaid grade level for English text, plus word/sentence/syllable counts.
try in playground →Token count
POST /api/token-countCount exact LLM tokens for a string using the real OpenAI BPE (o200k_base for gpt-4o/o-series, cl100k_base.
try in playground →Text chunk (RAG)
POST /api/text-chunkSplit text into overlapping chunks for RAG ingestion - by characters (default) or by exact LLM tokens.
try in playground →Readability score
POST /api/readability-scoreCompute Flesch-Kincaid Grade Level, Flesch Reading Ease, Gunning Fog Index, and Automated Readability Index from text.
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