{"uid":"cap_nhhyiHSq5ITx_Io-N3tLP","slug":"x402-tanship-dev-multilingual-text-embeddings-62787422","name":"x402.tanship.dev Multilingual Text Embeddings","description":"Payment-gated AI and browser automation API using the x402 protocol. All /v1/* endpoints require USDC payment on Base (eip155:8453) via x402 v2 exact scheme.","url":"https://x402.tanship.dev/v1/ai/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":{"properties":{}},"type":{"type":"string","const":"http"},"method":{"enum":["POST"],"type":"string"},"bodyType":{"enum":["json","form-data","text"],"type":"string"}},"additionalProperties":false}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","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":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_KIq6aXBELCIuOdkNDQq7K","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Generates 1024-dimensional multilingual text embeddings using the BGE-M3 model via edge AI","exampleAgentPrompt":"Turn this paragraph into a 1024-dimensional BGE-M3 embedding so I can store it in my vector database: 'The quick brown fox jumps over the lazy dog.'","exampleUseCases":[{"title":"Semantic search over multilingual documents","prompt":"Embed this English query so I can find semantically similar documents in my multilingual vector index: 'climate change effects on agriculture'"},{"title":"Duplicate detection in support tickets","prompt":"Convert these two customer support messages into embeddings so I can measure how similar they are and decide if they should be merged: 'My order never arrived' and 'I never received my package'"},{"title":"RAG pipeline document indexing","prompt":"Generate a BGE-M3 embedding for this Spanish text so I can add it to my retrieval-augmented generation knowledge base: 'El cambio climático afecta a la producción agrícola mundial'"}],"resultDescription":"Returns a 1024-dimensional float vector (BGE-M3 embedding) representing the semantic content of the input text, suitable for cosine similarity, vector database storage, or downstream ML tasks.","failureModes":["Empty or missing 'input' body returns a 400/422 validation error","Oversized input text exceeding model context window may be truncated or rejected","Network timeouts at edge node under high load","Invalid bodyType enum value causes schema validation failure","Non-UTF-8 encoded text may cause processing errors"],"whenToPreferThis":"Choose this endpoint when you need high-quality multilingual text embeddings (1024 dims) from the BGE-M3 model without running your own GPU infrastructure. It is ideal for RAG pipelines, semantic search, and cross-lingual similarity tasks where language coverage matters. Prefer it over OpenAI embeddings when you want a pay-per-call USDC micropayment model via x402 with no monthly subscription, or when BGE-M3's multilingual capabilities are specifically required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-13T18:45:49.737Z","isFirstParty":false}