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Delx Seeded Train-Test Split
x402
Delx Seeded Train-Test Split is a paid API for AI agents from api.delx.ai, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-13).
Splits a list of integer items into reproducible train and test sets using a deterministic seed and a specified test fraction.
Price / call$0.001
Success—
StatusUnknown
How this service works
Seeded Train Test Split: Seeded Train Test Split splits items into reproducible train and test sets from bounded caller-supplied values without an external provider. Call Seeded Train Test Split when an agent needs a reproducible decision that another run can independently replay. Returns the deterministic selection plus seed provenance, population bounds, and the operation-specific outcome for Seeded Train Test Split as versioned deterministic JSON. Price: $0.001 USDC via x402 on Base. First-p…
Output
Returns a JSON object with two arrays: 'train' containing the training subset and 'test' containing the test subset of the original integer items, along with operation metadata, an evidence block confirming no data retention and no external calls, and a SHA-256 hash of the input for auditability.
Example use cases
Reproducible ML dataset partitioning
“I have a list of sample IDs [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] and I need to split them into train and test sets with 20% for testing — use seed 'experiment-42' so I always get the same split.”
Cross-run experiment consistency
“For my experiment tracking, partition items [10, 20, 30, 40, 50, 60] into train and test with a 0.3 test fraction and seed 'run-seed-7' so my collaborator can reproduce the exact same split.”
Evaluation set isolation for batch scoring
“Take this list of record IDs [101, 102, 103, 104, 105, 106, 107, 108] and carve out 25% as a test set using seed 'holdout-v1' — I want the holdout to be stable across pipeline reruns.”
Technical details
Endpoint
POSThttps://api.delx.ai/api/v1/x402/seeded-train-test-splitWhen to prefer
Prefer this endpoint when you need a lightweight, stateless, reproducible train-test split for a small list of integers (up to 256 items) within an agent workflow — especially when auditability matters, since the response includes input hashes and confirms no external calls or data retention. It is ideal for pipelines that must produce identical splits across runs given the same seed and fraction.
Side effects
- Invalid seed type (non-string) returns validation error
- test_fraction outside [0,1] range causes computation failure
- items array exceeds 256-element limit returns 400 error
- Malformed request body returns schema validation error
- Empty items array may return empty train or test sets
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| seed | string | Seed supplied to Seeded Train Test Split; used only for this bounded calculation and processed in memory without retention. |
| items | array | Items supplied to Seeded Train Test Split; used only for this bounded calculation and processed in memory without retention. |
| test_fraction | number | Test Fraction supplied to Seeded Train Test Split; used only for this bounded calculation and processed in memory without retention. |
Output
Schema · Response
{
"type": "json",
"example": {
"result": {
"test": [
5
],
"train": [
1,
3,
2,
4
]
},
"schema": "delx/util-seeded-train-test-split/v1",
"status": "pass",
"evidence": {
"retained": false,
"input_sha256": "0584495460669e5b8cdc192403f94897df5ed2ef02ef94dff1c52727c63d9fe5",
"external_calls": 0
},
"operation": "seeded_decision:seeded_train_test_split"
}
}Tags
x402
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