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Relaystation RAG Query Bundle
x402
Relaystation RAG Query Bundle is a paid API for AI agents from api.relaystation.ai, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-14).
One-call RAG pipeline: embeds a question, searches a vector memory index, and optionally returns a grounded answer with cited source chunks
Price / call$0.01
Success—
StatusUnknown
How this service works
~$0.01/run, bills the sum of steps. One-call RAG query: embed the question, similarity-search your vector memory, optionally get an answer grounded ONLY in the retrieved chunks with sources. Recipe: relaystation.ai/recipes/agent-rag-memory. 1¢ x402 min; remainder auto-credits — relaystation.ai/penny
Output
Returns the most similar vector chunks from the index matching the query, plus an optional LLM-generated answer grounded exclusively in those retrieved chunks with source references included.
Example use cases
Customer support knowledge base lookup
“Query my Relaystation vector memory with 'how do I reset my password?' and return an answer grounded only in what's stored there, with the source passages cited.”
Legal document clause retrieval
“Search my embedded contract documents for the most relevant chunks about 'indemnification obligations' and give me a grounded summary with sources.”
Agent long-term memory recall
“Check my agent's vector memory index for anything relevant to 'previous user preferences for dashboard layout' and return the top matching chunks with a grounded answer.”
Technical details
Endpoint
POSThttps://api.relaystation.ai/v1/bundles/rag-queryWhen to prefer
Choose this endpoint when you need a complete one-call RAG pipeline — embedding, vector search, and optional grounded answer — without wiring together separate embedding and search services. Ideal for agents that have pre-populated a Relaystation baton vector index and need fast, cited, document-grounded responses rather than open-ended generation.
Side effects
- Empty or missing vector index returns no results or an error
- Poorly formed question yields low-similarity chunks with irrelevant content
- Payment not attached or insufficient USDC credits results in 402 rejection
- Malformed HTTP body type or missing required fields returns a 400 validation error
- Index not yet populated (no embeddings written) returns empty results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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