{"uid":"cap_JCuoHDAs0bFEnTofLY6gL","slug":"pagos-andreax-dev-extraer-json-desde-texto-libre-64b08c4c","name":"pagos.andreax.dev – Extraer JSON desde texto libre","description":"Extrae datos estructurados de un texto libre y los devuelve como JSON. Úsalo para parsear texto a datos. input=texto.","url":"https://pagos.andreax.dev/api/taller/peaje/extraer-json","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method"],"properties":{"type":{"type":"string","const":"http"},"method":{"enum":["GET","HEAD","DELETE"],"type":"string"},"queryParams":{"type":"object","required":["input"],"properties":{"input":{"type":"string","description":"texto del que extraer datos"}}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.004","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":"$0.004/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.004","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.004","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_36EmY4mMO0gcrIgYw89NY","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.004","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Parses free-form text into structured JSON by extracting key data fields using an LLM-backed extraction pipeline","exampleAgentPrompt":"Can you extract the structured data from this text and give it back to me as JSON: 'John Smith, born 12 March 1985, ordered 3 units of item SKU-4421 for delivery to 45 Oak Street, Madrid'?","exampleUseCases":[{"title":"Parse invoice text to JSON","prompt":"I have this raw invoice text: 'Invoice #1042, client Acme Corp, date 2024-06-01, total $4,320.00, due in 30 days' — can you extract all the fields and give me a structured JSON object?"},{"title":"Structure user form submission","prompt":"A user submitted this free-text support request: 'My name is Laura Gómez, email laura@example.com, issue: the login button is broken on Chrome v124 since yesterday.' Extract the structured fields like name, email, and issue description as JSON."},{"title":"Extract contact details from email body","prompt":"Here's an email signature block: 'Carlos Ruiz | Senior Developer | Telefónica España | +34 612 345 678 | carlos.ruiz@telefonica.es' — pull out the name, role, company, phone, and email as a JSON object."}],"resultDescription":"Returns a JSON object containing the structured data fields extracted from the input text. The specific keys and values depend on the content of the input — the endpoint infers the relevant fields and organises them as a machine-readable JSON structure.","failureModes":["Empty or very short input text may yield an empty or minimal JSON object","Highly ambiguous text may produce inconsistently structured output across calls","Non-Spanish/non-English text may be extracted with reduced accuracy depending on underlying model","Malformed or extremely noisy input may result in partial extraction missing some fields","Rate limiting or payment failure returns HTTP 402 requiring USDC payment via x402 protocol"],"whenToPreferThis":"Choose this endpoint when you need to convert unstructured or free-form natural language text into a structured JSON object without knowing the schema ahead of time. It is especially useful for ad-hoc extraction tasks where you want the model to infer the relevant fields automatically. Prefer it over schema-driven parsers when the text format varies and you need flexibility. It complements sibling endpoints on the same platform (sentiment, spelling correction, embeddings) for lightweight NLP pipelines.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T06:42:53.139Z","isFirstParty":false}