GEDX402 Vector Upsert

x402

GEDX402 Vector Upsert is a paid API for AI agents from ged-x402-search.jvalamis.workers.dev, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-15).

Inserts or updates a document (by text or raw vector) into a named vector namespace, returning the count of upserted records.

Price / call$0.02

Seller volume →—

Success—

StatusUnknown

How this service works

x402 workers ai. pay with usdc on base, polygon, arbitrum, world, or solana. no api keys.

Output

A JSON object with an 'upserted' integer field indicating how many vectors were successfully inserted or updated in the specified namespace.

Example use cases

Example prompt

“Store this product description in my 'catalog-2024' namespace with id 'prod-789': 'Lightweight waterproof hiking boots with Vibram sole, available in sizes 6-13.' — include metadata {category: 'footwear', brand: 'TrailForce'}.”

Technical details

Endpoint

GEThttps://ged-x402-search.jvalamis.workers.dev/v1/vector/upsert

When to prefer

Use this endpoint when you need to add or update documents in a persistent vector store accessible via x402 micropayments, without managing API keys. Ideal for agent memory systems, RAG pipelines, or semantic search indexes where you want per-call billing in USDC across multiple chains. Prefer this over self-hosted vector DBs when you want zero-infrastructure embedding + storage in one call.

Side effects

Missing required 'id' or 'text' field returns an error
Namespace string outside 2-64 character range is rejected
Vector dimensions not matching 768 dims cause a schema mismatch error
Payment not settled via x402 results in 402 Payment Required response
Malformed metadata object may cause silent partial failure or rejection
Providing both 'text' and 'vectors' fields simultaneously may cause ambiguous behavior

Input

Schema · Request body

Field	Type	Description
vectors	array
namespace	string

Output

Schema · Response

{
  "type": "json",
  "example": {
    "upserted": 1
  }
}

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Technical details

Endpoint

GEThttps://ged-x402-search.jvalamis.workers.dev/v1/vector/upsert

When to prefer

Side effects

Missing required 'id' or 'text' field returns an error
Namespace string outside 2-64 character range is rejected
Vector dimensions not matching 768 dims cause a schema mismatch error
Payment not settled via x402 results in 402 Payment Required response
Malformed metadata object may cause silent partial failure or rejection
Providing both 'text' and 'vectors' fields simultaneously may cause ambiguous behavior

Input

Schema · Request body

Field	Type	Description
vectors	array
namespace	string

Output

Schema · Response

{
  "type": "json",
  "example": {
    "upserted": 1
  }
}