{"uid":"cap_nohJVG7LwAxFr395rxgbj","slug":"gedx402-vector-search-batch-upsert-7779bcd2","name":"GEDX402 Vector Search Batch Upsert","description":"x402 workers ai. pay with usdc on base, polygon, arbitrum, world, or solana. no api keys.","url":"https://ged-x402-search.jvalamis.workers.dev/v1/search/upsert/batch","method":"GET","headers":{},"bodySchema":{"type":"object","properties":{"documents":{"type":"array","items":{"type":"object"}},"namespace":{"type":"string"}}},"responseSchema":{"type":"json","example":{"upserted":2}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.06","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"settled","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.06/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.06","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.06","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_rBxbmJoICgdghqXbB-tn3","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.06","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Batch-upserts documents (text + optional metadata) into a vector store index, embedding and storing them for later semantic search retrieval.","exampleAgentPrompt":"Batch-index these 3 documents into the 'project-alpha' namespace so I can search them later: doc1 'The transformer architecture uses self-attention', doc2 'BERT is a bidirectional encoder', doc3 'GPT uses autoregressive decoding' — include their source metadata.","exampleUseCases":null,"resultDescription":"A JSON object with an 'upserted' field indicating how many documents were successfully embedded and stored, e.g. {\"upserted\": 2}.","failureModes":["Invalid or missing namespace (must be 2-64 chars) returns validation error","Documents missing required 'id' or 'text' fields return schema error","Payment failure or insufficient USDC balance returns 402","Vector dimension mismatch (not 768 dims) causes upsert rejection","Empty documents array returns zero upserted","Namespace conflict or quota exceeded returns server error"],"whenToPreferThis":"Use this endpoint when you need to add or update multiple documents at once into a persistent vector store without managing API keys, paying per-call in USDC via x402. Prefer this over single-document upsert when ingesting batches of 2+ documents to reduce round-trips. Choose this over self-hosted solutions when you want a serverless, pay-as-you-go vector index on Cloudflare's global edge.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T12:31:57.463Z","isFirstParty":false}