{"slug":"402utils-com-v1-embed-19574e","title":"Text → vector embeddings via Cloudflare Workers AI","host":"402utils.com","method":"POST","resource":"https://402utils.com/v1/embed","category":"other","description":"Text → vector embeddings via Cloudflare Workers AI. Send {text} or {texts[]} (≤20, each ≤4000 chars); returns one float vector per input. Default model @cf/baai/bge-m3 (1024-dim, multilingual). The model is named in the response — embeddings only compare within the same model. Completes the RAG chai","price_listed":0.004,"price_asked":null,"state":"effects","state_label":"Not tested: has real-world effects","checks_7d":0,"answered_7d":0,"latency_ms_median":null,"reported_calls_30d":1,"reported_payers_30d":1,"networks":["eip155:8453"],"badge":"unverified","paid_checks_7d":0,"paid_ok_7d":0,"example_input":{"body":{"texts":["A cat sat on the mat.","A feline rested on the rug."]},"bodyType":"json","method":"POST","type":"http"},"output_schema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{"input":{"additionalProperties":false,"properties":{"body":{"description":"Provide exactly one of `text` or `texts`.","properties":{"model":{"default":"@cf/baai/bge-m3","description":"Embedding model. Default @cf/baai/bge-m3. en-v1.5 models are English-only, 512-token max.","enum":["@cf/baai/bge-m3","@cf/baai/bge-base-en-v1.5","@cf/baai/bge-large-en-v1.5","@cf/baai/bge-small-en-v1.5"],"type":"string"},"text":{"description":"A single text to embed (≤ 4000 chars).","type":"string"},"texts":{"description":"Up to 20 texts to embed in one call (each ≤ 4000 chars).","items":{"type":"string"},"maxItems":20,"type":"array"}},"type":"object"},"bodyType":{"enum":["json","form-data","text"],"type":"string"},"method":{"enum":["POST"],"type":"string"},"type":{"const":"http","type":"string"}},"required":["type","method","bodyType","body"],"type":"object"},"output":{"properties":{"example":{"additionalProperties":false,"properties":{"dimensions":{"description":"Length of each vector (bge-m3 → 1024).","type":"integer"},"embeddings":{"description":"One vector per input text, in request order.","items":{"items":{"type":"number"},"type":"array"},"type":"array"},"model":{"description":"The model used (compare embeddings only within one model).","type":"string"},"usage":{"properties":{"inputs":{"description":"Number of texts embedded in this call.","type":"integer"}},"required":["inputs"],"type":"object"}},"required":["embeddings","model","dimensions","usage"],"type":"object"},"type":{"type":"string"}},"required":["type"],"type":"object"}},"required":["input"],"type":"object"},"history":[],"description_full":"Text → vector embeddings via Cloudflare Workers AI. Send {text} or {texts[]} (≤20, each ≤4000 chars); returns one float vector per input. Default model @cf/baai/bge-m3 (1024-dim, multilingual). The model is named in the response — embeddings only compare within the same model. Completes the RAG chain: readability → chunk → embed, no OpenAI account. Cosine-compare the vectors yourself. Unavailable model/binding → 503, not billed.","last_updated":"2026-10-03T05:11:23.253Z","schemes":["exact"]}