74trust / 100
Assistant Sector Ml Task Type Per Label
by market.datapackvibe.com in Productivity & SaaS
x402 APIPassing, checked 3 h ago
Task type - Per-label precision and recall: Per-label precision and recall for Task type. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded per-label precision and recall deliverable.
POST https://market.datapackvibe.com/x402/assistant-sector-ml-task-type-per-label
Last 30 days
All checks passedSome failedAll failedNot checked
- Uptime
- 87.5%
- Response time
- 182 ms typical, 398 ms slowest 5%
- Last check
- 3 h ago
- Next check
- any minute now
How to call it
# See the payment challenge (nothing is charged)
curl -i -X POST "https://market.datapackvibe.com/x402/assistant-sector-ml-task-type-per-label" \
-H "content-type: application/json" \
-d '{"records":[{"actual":"research","id":"example-0-0","predicted":"research","text":"research sample document number 0 for this supplied dataset."},{"actual":"research","id":"example-0-1","predicted":"research","text":"research sample document number 1 for this supplied dataset."},{"actual":"research","id":"example-0-2","predicted":"research","text":"research sample document number 2 for this supplied dataset."},{"actual":"writing","id":"example-1-0","predicted":"writing","text":"writing sample document number 0 for this supplied dataset."},{"actual":"writing","id":"example-1-1","predicted":"writing","text":"writing sample document number 1 for this supplied dataset."},{"actual":"writing","id":"example-1-2","predicted":"writing","text":"writing sample document number 2 for this supplied dataset."},{"actual":"analysis","id":"example-2-0","predicted":"analysis","text":"analysis sample document number 0 for this supplied dataset."},{"actual":"analysis","id":"example-2-1","predicted":"analysis","text":"analysis sample document number 1 for this supplied dataset."},{"actual":"analysis","id":"example-2-2","predicted":"analysis","text":"analysis sample document number 2 for this supplied dataset."},{"actual":"implementation","id":"example-3-0","predicted":"implementation","text":"implementation sample document number 0 for this supplied dataset."},{"actual":"implementation","id":"example-3-1","predicted":"implementation","text":"implementation sample document number 1 for this supplied dataset."},{"actual":"implementation","id":"example-3-2","predicted":"implementation","text":"implementation sample document number 2 for this supplied dataset."}]}'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%2Fmarket.datapackvibe.com%2Fx402%2Fassistant-sector-ml-task-type-per-label
const res = await pay("https://market.datapackvibe.com/x402/assistant-sector-ml-task-type-per-label", {
method: "POST",
headers: { "content-type": "application/json" },
body: JSON.stringify({"records":[{"actual":"research","id":"example-0-0","predicted":"research","text":"research sample document number 0 for this supplied dataset."},{"actual":"research","id":"example-0-1","predicted":"research","text":"research sample document number 1 for this supplied dataset."},{"actual":"research","id":"example-0-2","predicted":"research","text":"research sample document number 2 for this supplied dataset."},{"actual":"writing","id":"example-1-0","predicted":"writing","text":"writing sample document number 0 for this supplied dataset."},{"actual":"writing","id":"example-1-1","predicted":"writing","text":"writing sample document number 1 for this supplied dataset."},{"actual":"writing","id":"example-1-2","predicted":"writing","text":"writing sample document number 2 for this supplied dataset."},{"actual":"analysis","id":"example-2-0","predicted":"analysis","text":"analysis sample document number 0 for this supplied dataset."},{"actual":"analysis","id":"example-2-1","predicted":"analysis","text":"analysis sample document number 1 for this supplied dataset."},{"actual":"analysis","id":"example-2-2","predicted":"analysis","text":"analysis sample document number 2 for this supplied dataset."},{"actual":"implementation","id":"example-3-0","predicted":"implementation","text":"implementation sample document number 0 for this supplied dataset."},{"actual":"implementation","id":"example-3-1","predicted":"implementation","text":"implementation sample document number 1 for this supplied dataset."},{"actual":"implementation","id":"example-3-2","predicted":"implementation","text":"implementation sample document number 2 for this supplied dataset."}]}),
});
console.log(await res.json());Example input
{
"records": [
{
"actual": "research",
"id": "example-0-0",
"predicted": "research",
"text": "research sample document number 0 for this supplied dataset."
},
{
"actual": "research",
"id": "example-0-1",
"predicted": "research",
"text": "research sample document number 1 for this supplied dataset."
},
{
"actual": "research",
"id": "example-0-2",
"predicted": "research",
"text": "research sample document number 2 for this supplied dataset."
},
{
"actual": "writing",
"id": "example-1-0",
"predicted": "writing",
"text": "writing sample document number 0 for this supplied dataset."
},
{
"actual": "writing",
"id": "example-1-1",
"predicted": "writing",
"text": "writing sample document number 1 for this supplied dataset."
},
{
"actual": "writing",
"id": "example-1-2",
"predicted": "writing",
"text": "writing sample document number 2 for this supplied dataset."
},
{
"actual": "analysis",
"id": "example-2-0",
"predicted": "analysis",
"text": "analysis sample document number 0 for this supplied dataset."
},
{
"actual": "analysis",
"id": "example-2-1",
"predicted": "analysis",
"text": "analysis sample document number 1 for this supplied dataset."
},
{
"actual": "analysis",
"id": "example-2-2",
"predicted": "analysis",
"text": "analysis sample document number 2 for this supplied dataset."
},
{
"actual": "implementation",
"id": "example-3-0",
"predicted": "implementation",
"text": "implementation sample document number 0 for this supplied dataset."
},
{
"actual": "implementation",
"id": "example-3-1",
"predicted": "implementation",
"text": "implementation sample document number 1 for this supplied dataset."
},
{
"actual": "implementation",
"id": "example-3-2",
"predicted": "implementation",
"text": "implementation sample document number 2 for this supplied dataset."
}
]
}Example output
{
"files": [],
"order_id": "ord_example",
"result": {
"completed": true,
"workflow": "sector-ml-task-type-per-label"
},
"sku": "assistant-sector-ml-task-type-per-label",
"status": "delivered"
}Security scan
- No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.
Recent checks
| When | Result | HTTP | Time | Price |
|---|---|---|---|---|
| 3 h ago | Passed | 402 | 81 ms | $0.01 |
| 7 h ago | Passed | 402 | 59 ms | $0.01 |
| 11 h ago | Timed out | - | - | - |
| 14 h ago | Passed | 402 | 852 ms | $0.01 |
| 18 h ago | Passed | 402 | 182 ms | $0.01 |
| 22 h ago | Passed | 402 | 398 ms | $0.01 |
| 25 h ago | Passed | 402 | 66 ms | $0.01 |
| 30 h ago | Passed | 402 | 196 ms | $0.01 |