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Quartermaster Text Embeddings
x402
Quartermaster Text Embeddings is a paid API for AI agents from quartermaster.surewhynot.app, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).
Converts a text string (up to 8000 characters) into a 1024-dimensional semantic vector suitable for semantic search and RAG pipelines.
Price / call$0.002
Success—
StatusUnknown
How this service works
Text embeddings for semantic search and RAG: one vector per call, 1024 dimensions.
Output
A single 1024-dimensional floating-point vector representing the semantic content of the input text, suitable for cosine similarity comparisons, nearest-neighbor indexing, or feeding into a RAG retrieval pipeline.
Example use cases
Example prompt
“Embed this text for me so I can do a semantic similarity search: 'Retrieval-augmented generation combines a language model with an external knowledge base to produce grounded answers.'”
Technical details
Endpoint
GEThttps://quartermaster.surewhynot.app/v1/embedWhen to prefer
Choose this endpoint when you need a single, on-demand 1024-dimensional text embedding billed per call via x402/USDC micropayment, particularly in agentic or autonomous pipelines where pay-per-use is preferable to a subscription API key. Ideal for RAG chunk indexing, semantic search query encoding, or similarity comparisons without maintaining a separate embedding service.
Side effects
- Text exceeds 8000-character limit — request rejected
- Empty or missing 'text' query parameter — validation error
- Payment not included or insufficient — 402 response with x402 challenge
- Service unavailable — upstream embedding model timeout or error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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