{"uid":"cap_JU1zWpwvaW4uWIrSkzJQE","slug":"scopeapi-dev-text-embeddings-af3a6d0c","name":"scopeapi.dev Text Embeddings","description":"Text Embeddings","url":"https://scopeapi.dev/embeddings","method":"POST","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method","bodyType","body"],"properties":{"body":{"required":["input"],"properties":{"input":{"oneOf":[{"type":"string"},{"type":"array","items":{"type":"string"},"maxItems":16,"minItems":1}]}}},"type":{"type":"string","const":"http"},"method":{"enum":["POST"],"type":"string"},"bodyType":{"enum":["json","form-data","text"],"type":"string"}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":{"type":"json","example":{"model":"text-embedding-3-small","usage":{"totalTokens":6,"promptTokens":6},"endpoint":"/embeddings","dimensions":1536,"embeddings":[{"index":0,"embedding":[0.0123,-0.0456,0.0789]}]}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.003","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","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":"$0.003/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_50lm8nN5Ek5X7SIfLdgnB","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.003","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Converts one or more text strings into high-dimensional vector embeddings using a 1536-dimension model","exampleAgentPrompt":"Convert this sentence into a text embedding vector: 'The quick brown fox jumps over the lazy dog' — I need the 1536-dimension float array to store in my vector database.","exampleUseCases":[{"title":"Semantic search index population","prompt":"I need to embed these 10 product descriptions so I can store them in my Pinecone vector database and do semantic similarity search: ['Wireless noise-cancelling headphones', 'Bluetooth earbuds with mic', 'Over-ear studio monitor headphones', ...]"},{"title":"RAG document chunking pipeline","prompt":"Take this paragraph and turn it into a vector embedding so I can add it to my retrieval-augmented generation knowledge base: 'Climate change refers to long-term shifts in global temperatures and weather patterns.'"},{"title":"Duplicate content detection","prompt":"Generate embeddings for both of these sentences so I can compare their cosine similarity and check if they mean the same thing: 'How do I reset my password?' and 'What steps do I take to change my login credentials?'"}],"resultDescription":"Returns a JSON object containing the model name (text-embedding-3-small), the number of dimensions (1536), token usage statistics (prompt tokens and total tokens), and an array of embedding objects each with an index and a floating-point vector array representing the semantic content of the input text.","failureModes":["Input array exceeds 16 items (maxItems constraint violated)","Empty input array (minItems:1 not satisfied)","Malformed JSON body causing parse error","Token limit exceeded for very long input strings","Payment failure via x402 protocol returning 402 status","Network timeout for large batch requests"],"whenToPreferThis":"Choose this endpoint when you need fast, affordable text vectorization via a pay-per-call x402 micropayment model without managing API keys. It is ideal for agents that need to embed text on-demand within a pipeline, store vectors in a database, or perform semantic similarity at $0.003 per call. Prefer this over raw OpenAI API access when operating in an agentic marketplace context where x402 payments are already wired in.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T06:36:26.737Z","isFirstParty":false}