Delx Commerce — Multilingual Text Ranking API is a paid API for AI agents from commerce.delx.ai, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-02).
Ranks a list of candidate texts against a multilingual query using semantic similarity scoring, returning candidates ordered by relevance score.
Pay-per-result APIs for agents. No signup. Exact price. Verifiable delivery. USDC on Base + Solana via x402.
A JSON object containing a ranked array of candidate objects, each with a floating-point similarity score and the original zero-based candidate_index. Also includes the model name (multilingual-e5-large), a SHA256 hash of the result for verifiability, a URL to retrieve the stored ranking, input SHA256, generation ID, candidate count, sale price in USDC, and cost breakdown.
POSThttps://commerce.delx.ai/api/v1/x402/rank-multilingual-texts?utm_source=zero.xyzChoose this endpoint when you need semantic relevance ranking across multiple languages without building or hosting your own embedding model. It is ideal for multilingual RAG pipelines, cross-lingual FAQ retrieval, or reranking search results where candidates may span languages. Prefer it over monolingual rankers when your corpus or users are multilingual. The pay-per-call model ($0.003 USDC, no signup) is optimal for agent workflows with variable or unpredictable load, and the verifiable SHA256 delivery and stored ranking URL make it suitable for auditable pipelines.
| Field | Type | Description |
|---|---|---|
| query | string | The multilingual search question or intent to rank against. |
| candidates | array | Unique candidate texts; returned by original zero-based index. |
{
"type": "json",
"example": {
"model": "beautyyuyanli/multilingual-e5-large",
"ranked": [
{
"score": 0.912314,
"candidate_index": 1
},
{
"score": 0.134221,
"candidate_index": 0
}
],
"sha256": "2d6c7c2b3f3c8e1e7b0d3a5b6e7f8a9b1234567890abcdef1234567890abcdef",
"provider": "replicate",
"media_type": "application/json",
"ranking_url": "https://api.delx.ai/api/v1/generated-rankings/ranking-example.json",
"input_sha256": "34a8815e9c57e321194d50f2ea8b64394019fb8038c9aefd7a9a306a5030fc31",
"generation_id": "ranking-example-generation-id",
"candidate_count": 2,
"sale_price_usdc": 0.003,
"gross_margin_usd": 0.002025,
"upstream_cost_usd": 0.000975
}
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