ToolVet
80trust / 100

Embed

by Combify Compute in AI models & inference

x402 APIPassing, checked 4 h ago

Semantic search building block: turns text into a 1024-number vector for RAG retrieval, dedup, and clustering (bge-m3), fixed price $0.005 USDC. Use this when comparing meaning between texts, not for answers (use /chat) or translation (use /translate). POST JSON body {text (required, max 8000 chars)}. Returns {embedding, dimensions}. Unpaid calls get 402; paid calls settle only on success.

POST https://compute.combify.app/embed

Last 30 days

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Uptime
100%
Response time
245 ms typical, 245 ms slowest 5%
Last check
4 h ago
Next check
any minute now

How to call it

# See the payment challenge (nothing is charged)
curl -i -X POST "https://compute.combify.app/embed" \
  -H "content-type: application/json" \
  -d '{"text":"hello world"}'
import { wrapFetchWithPayment } from "@x402/fetch";
import { x402Client } from "@x402/core/client";
import { ExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

const client = new x402Client().register(
  "eip155:8453",
  new ExactEvmScheme(privateKeyToAccount(process.env.AGENT_KEY)),
);
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? Preflight it first for $0.005:
// GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fcompute.combify.app%2Fembed
const res = await pay("https://compute.combify.app/embed", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({"text":"hello world"}),
});
console.log(await res.json());

Example input

{
  "text": "hello world"
}

Example output

{
  "dimensions": 1024,
  "embedding": [
    0.012,
    -0.034,
    0.056
  ],
  "est_cost_usd": 0.00001,
  "model": "@cf/baai/bge-m3"
}

Security scan

  • No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.

Recent checks

WhenResultHTTPTimePrice
4 h agoPassed402245 ms$0.005