{"slug":"quickbuild-quynguyenbac-workers-dev-v1-embeddings-4570e3","title":"Drop-in OpenAI Embeddings endpoint","host":"quickbuild.quynguyenbac.workers.dev","method":"GET","resource":"https://quickbuild.quynguyenbac.workers.dev/v1/embeddings","category":"market","description":"Drop-in OpenAI Embeddings endpoint: POST {input: string | string[], model, encoding_format: float|base64, dimensions} and get {object: \"list\", data: [{embedding, index}], model, usage}. Models (Cloudflare Workers AI): bge-m3 (1024-d, multilingual (100+ languages), 8192-token context); bge-large-en-v","price_listed":0.001,"price_asked":0.001,"state":"answering","state_label":"Answering","checks_7d":1,"answered_7d":1,"latency_ms_median":59,"reported_calls_30d":1,"reported_payers_30d":1,"networks":["eip155:8453"],"badge":"unverified","paid_checks_7d":0,"paid_ok_7d":0,"example_input":{"method":"GET","queryParams":{"input":["x402 lets AI agents pay for APIs per call.","Vector search over documents"],"model":"bge-m3"},"type":"http"},"output_schema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{"input":{"additionalProperties":false,"properties":{"method":{"enum":["GET"],"type":"string"},"queryParams":{"properties":{"dimensions":{"description":"Optional output size; vectors are truncated and re-normalized.","maximum":1024,"minimum":1,"type":"integer"},"encoding_format":{"description":"float (default) or base64 (little-endian float32).","enum":["float","base64"],"type":"string"},"input":{"description":"Text or array of texts to embed (max 100). Optional: defaults to a sample sentence.","items":{"type":"string"},"type":["string","array"]},"model":{"description":"Embedding model alias (default bge-m3).","enum":["bge-m3","bge-large-en-v1.5","bge-base-en-v1.5","bge-small-en-v1.5","embeddinggemma-300m"],"type":"string"}},"required":[],"type":"object"},"type":{"const":"http","type":"string"}},"required":["type","method"],"type":"object"},"output":{"properties":{"example":{"properties":{"data":{"items":{"properties":{"embedding":{"items":{"type":"number"},"type":["array","string"]},"index":{"type":"integer"},"object":{"type":"string"}},"type":"object"},"type":"array"},"dimensions":{"type":"integer"},"model":{"type":"string"},"modelId":{"type":"string"},"object":{"type":"string"},"usage":{"properties":{"prompt_tokens":{"type":"integer"},"total_tokens":{"type":"integer"}},"type":"object"}},"type":"object"},"type":{"type":"string"}},"required":["type"],"type":"object"}},"required":["input"],"type":"object"},"history":[{"day":"2026-10-24","reachable":true,"status":402,"valid_402":true,"asked_usdc":0.001,"price_match":true,"latency_ms":59,"error":null}],"description_full":"Drop-in OpenAI Embeddings endpoint: POST {input: string | string[], model, encoding_format: float|base64, dimensions} and get {object: \"list\", data: [{embedding, index}], model, usage}. Models (Cloudflare Workers AI): bge-m3 (1024-d, multilingual (100+ languages), 8192-token context); bge-large-en-v1.5 (1024-d, English); bge-base-en-v1.5 (768-d, English); bge-small-en-v1.5 (384-d, English, fastest); embeddinggemma-300m (768-d, multilingual (Google EmbeddingGemma)). Any other model name (e.g....","last_updated":"2026-10-23T16:19:19.499Z","schemes":["exact"]}