{"uid":"cap_WHLuQimqmhoAtYXAlU9p0","slug":"citiview-bge-m3-embeddings-0690c4dd","name":"Citiview BGE-M3 Embeddings","description":"OpenAI-compatible embeddings endpoint (bge-m3, 1024 dimensions, 100+ languages): same request and response shape as OpenAI /v1/embeddings, including encoding_format base64. Up to 100 inputs per call, flat price, no API key: point any OpenAI SDK at https://agents.citiviewgroup.com/v1 and pay per request with x402. Priced by size and model: $0.003 + 3x the model token cost (bge-m3 is cheapest). Also callable as GET with the same fields as query parameters.","url":"https://agents.citiviewgroup.com/v1/embeddings?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","$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"],"type":"string"},"queryParams":{"type":"object","required":["input"],"properties":{"input":{"type":"string","description":"Text to embed (POST also accepts an array of up to 100 strings)"},"model":{"type":"string","description":"Ignored; always bge-m3"},"encoding_format":{"type":"string","description":"float (default) | base64"}}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.003","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":"$0.003/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_2aeNNcV1S-m9IKpRfHDBl","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.003","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Generates multilingual text embeddings (1024-dimensional BGE-M3 vectors) for up to 100 text inputs per call, using an OpenAI-compatible API shape.","exampleAgentPrompt":"Embed the following sentence into a 1024-dimensional vector using BGE-M3: 'The quick brown fox jumps over the lazy dog' — return it as a float array.","exampleUseCases":[{"title":"RAG pipeline document indexing","prompt":"I need to embed these 50 product descriptions so I can store them in my vector database for semantic search — can you vectorize all of them using BGE-M3 and return the float arrays?"},{"title":"Multilingual semantic similarity","prompt":"I have customer reviews in Spanish, French, and Japanese — embed each one so I can compare how semantically similar they are to a set of English reference sentences."},{"title":"No-key OpenAI SDK swap","prompt":"I want to switch my embedding calls from OpenAI to a pay-per-request service that uses BGE-M3 — just point my existing SDK at it and embed this text: 'summarize quarterly earnings trends'."}],"resultDescription":"Returns a JSON object in OpenAI /v1/embeddings response format: an array of embedding objects each containing an index, the embedding vector (as a float array or base64-encoded string depending on encoding_format), and object type 'embedding', plus a usage object with token counts and the model name 'bge-m3'.","failureModes":["Missing 'input' parameter returns a validation error","More than 100 inputs in a single call may be rejected","Invalid encoding_format value falls back to float silently or errors","Payment not provided or insufficient USDC causes 402 Payment Required","GET requests with very long input strings may hit URL length limits — use POST for large inputs","Network timeout if the model is cold-starting"],"whenToPreferThis":"Choose this endpoint when you need OpenAI-compatible embeddings without an OpenAI API key, want multilingual coverage across 100+ languages with a single model, prefer pay-per-call pricing with no subscription, or need to swap in a drop-in replacement for /v1/embeddings in an existing OpenAI SDK integration. BGE-M3's 1024-dimensional output is well-suited for dense retrieval and reranking tasks.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T06:48:17.962Z","isFirstParty":false,"canonicalSlug":"citiview-bge-m3-embeddings-0690c4dd"}