{"uid":"cap_vnoQpcib6RjHEDHBWmRJy","slug":"one-engine-t5-text-sentence-tokenizer-fe2685d0","name":"ONE Engine T5 Text Sentence 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/sentences/t5?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":"0.0025","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":"$0.0025/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0025","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0025","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_rd0W1iqT3YLHjUm8F0Ye0","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.0025","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Splits input text into individual sentences using a T5-based model, returning tokenized sentence boundaries.","exampleAgentPrompt":"Split this article into individual sentences using the T5 sentence tokenizer: 'The quick brown fox jumped over the lazy dog. It was a sunny afternoon. Nobody expected what happened next.'","exampleUseCases":[{"title":"NLP pipeline text preprocessing","prompt":"I have a 10,000-word research paper and I need it broken into individual sentences before I feed it into an embedding model — can you run it through the T5 sentence tokenizer for me?"},{"title":"Transcript segmentation for summarization","prompt":"Take this raw meeting transcript and split it into separate sentences so I can process each one individually for a summary: 'We discussed Q3 targets today. Revenue is up 12%. The team flagged three blockers.'"},{"title":"Chunking product reviews for analysis","prompt":"I've got a big block of customer feedback text — please segment it into individual sentences using the T5 sentence splitter so I can classify each sentence separately."}],"resultDescription":"A JSON object containing the input text split into an array of individual sentences, segmented using a T5-based sentence boundary detection model. The exact response structure may vary but typically includes the detected sentence units.","failureModes":["Text exceeding 50,000 characters may be rejected or truncated","Empty or whitespace-only text may return empty results","Non-standard punctuation or foreign language text may produce inaccurate sentence boundaries","Payment failure via x402 protocol blocks the request","Malformed JSON request body returns an error","Very short single-sentence inputs return a trivial single-element result"],"whenToPreferThis":"Choose this endpoint when you need lightweight, pay-per-call sentence tokenization without managing your own NLP infrastructure. It is ideal for agentic pipelines that need to pre-process text into sentence chunks before embedding, summarization, or classification — especially when cost-per-call billing via USDC on Base is preferred over subscription APIs. Best for one-off or low-volume sentence segmentation tasks where spinning up a local NLP model is overkill.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-02T12:43:57.137Z","isFirstParty":false,"canonicalSlug":"one-engine-t5-text-sentence-tokenizer-fe2685d0"}