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uxus.finance Text Embedding API
x402
uxus.finance Text Embedding API is a paid API for AI agents from uxus.finance, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-14).
Generates a 1024-dimensional jina-embeddings-v3 vector for each input string (up to 64 strings per call), returning embeddings with dimension count and token usage.
Price / call$0.01
Success—
StatusUnknown
How this service works
Text embeddings for AI agents — no API key, no account, no signup; pay per call in USDC on Base. POST JSON { input: string or string[] (max 64 per call) }. Model is jina-embeddings-v3, 1024 dimensions, retrieval.passage task. Returns { model, embeddings (one vector per input), dimensions, count, usage, latency_ms }. For agents building a vector index or doing semantic search without a Jina or OpenAI key.
Output
Returns an array of 1024-dimensional float vectors (one per input string), along with the dimension count (1024) and token usage statistics for the batch call.
Example use cases
Semantic search index population
“Take these 50 FAQ answers and turn them into 1024-dim embeddings so I can index them in my vector store for semantic search retrieval.”
Duplicate product detection
“Embed these two product titles — 'Men's Running Sneakers Size 10' and 'Athletic Running Shoes for Men Size 10' — and give me their vectors so I can check how similar they are.”
RAG document chunking pipeline
“I have these 20 text chunks from my knowledge base — can you convert each one to a jina-embeddings-v3 vector so I can load them into Pinecone?”
Technical details
Endpoint
POSThttps://uxus.finance/api/embedWhen to prefer
Choose this endpoint when you need jina-embeddings-v3 specifically (1024-dim, strong multilingual and retrieval performance), can batch up to 64 strings per call, and want a pay-per-call model via x402/USDC without subscription overhead. Prefer over OpenAI or Cohere embeddings when you want jina's model quality and the x402 micropayment model fits your stack.
Side effects
- Batch exceeds 64 strings — request rejected with error
- Empty input array or null strings — validation error returned
- Input strings too long for model token limit — truncation or error
- Payment failure via x402 protocol — 402 response with payment details
- Network timeout on large batches — partial or no response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | string | string[] | Text to embed, or an array of up to 64 strings. |
Output
Schema · Response
{
"type": "json",
"example": {
"count": 1,
"model": "jina-embeddings-v3",
"usage": {
"total_tokens": 8
},
"dimensions": 1024,
"embeddings": [
[
0.013,
-0.021,
0.005
]
],
"latency_ms": 300
}
}Tags
x402
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