{"uid":"cap_qmqdPFyJFyInhMHZhh5PN","slug":"one-engine-word-bigram-tokenizer-4f618e94","name":"ONE Engine Word Bigram Tokenizer","description":"Low-cost pay-per-call utility APIs for autonomous agents using x402 on Base.","url":"https://one-search.one-engine.workers.dev/v3/text-token/word-bigrams/t3?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","required":["text"],"properties":{"text":{"type":"string","description":"Text up to 50000 characters"}}},"responseSchema":{"type":"object","additionalProperties":true},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.001","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_DTExroKD8jNOI3thdDv2E","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.001","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Extracts all consecutive word bigrams (two-word pairs) from input text, returning tokenized n-gram data for NLP and text analysis tasks.","exampleAgentPrompt":"Extract all word bigrams from this text for me: 'The quick brown fox jumps over the lazy dog and the dog barked back.'","exampleUseCases":[{"title":"NLP feature engineering pipeline","prompt":"Take this product review corpus and extract all word bigrams so I can use them as features for my sentiment classification model."},{"title":"Keyword co-occurrence analysis","prompt":"I have this 10,000-word article about climate change — pull out all the word bigrams so I can see which terms appear together most frequently."},{"title":"Text preprocessing for search indexing","prompt":"Run bigram tokenization on this blog post content so I can index two-word phrases alongside single keywords in my search engine."}],"resultDescription":"A JSON object containing the extracted word bigrams from the input text — consecutive two-word pairs derived by sliding a window of size 2 across the tokenized words. May include bigram arrays or frequency maps depending on the API implementation.","failureModes":["Text exceeding 50,000 characters may be rejected or truncated","Empty or whitespace-only text may return an empty bigram list","Payment failure via x402 results in 402 response before processing","Malformed JSON body returns 400 error","Non-English or heavily punctuated text may yield unexpected tokenization results"],"whenToPreferThis":"Choose this endpoint when you need a cheap, fast, pay-per-call bigram extraction primitive for agentic NLP pipelines — particularly when you want no infrastructure overhead and are already using x402 micropayments on Base. Ideal for preprocessing steps in search indexing, feature engineering, or text analytics where you need raw bigram tokens without a full NLP framework.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-02T12:43:51.711Z","isFirstParty":false,"canonicalSlug":"one-engine-word-bigram-tokenizer-1a5f1bd9"}