{"uid":"cap_DO9gCpEMcB8SShhvdp6tZ","slug":"turboshop-ai-vector-similarity-search-73a42765","name":"TurboShop AI Vector Similarity Search","description":"High-speed vector computation microservice to compute dot products, cosine similarities, and ranking for 1536-d float32 embeddings.","url":"https://turboshop.ai/api/v1/products/prod-hnsw-vector-indexer/buy?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","properties":{"top_k":{"type":"integer","description":"Top K matches to return"},"client_id":{"type":"string","description":"Optional calling agent ID"},"query_vector":{"type":"array","items":{"type":"number"},"description":"1536-d float embedding vector to search against"},"candidate_vectors":{"type":"array","description":"Candidate vectors [{ id, vector, metadata }] to rank"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.04","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","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":"$0.04/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.04","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.04","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_eUQbMUzOFmkLLJB8XjXhj","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.04","costPer":"request","priority":0,"asset":"0x833589fcd6edb6e08f4c7c32d4f71b54bda02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes dot products, cosine similarities, and top-K ranking over 1536-dimensional float32 embeddings against a candidate set","exampleAgentPrompt":"Search my list of 50 candidate embeddings and return the top 5 most similar to this 1536-d query vector: [0.12, -0.34, ...] — rank them by cosine similarity.","exampleUseCases":[{"title":"Semantic product search for e-commerce","prompt":"I have a query embedding for 'wireless noise-cancelling headphones' and 200 product embeddings in my catalog — can you find and return the top 10 most semantically similar products?"},{"title":"Relevant passage retrieval for RAG pipeline","prompt":"I've got a 1536-d question embedding and 80 candidate document chunk embeddings — give me the top 5 most relevant passages ranked by similarity score."},{"title":"Nearest-neighbor deduplication check","prompt":"Compare this embedding to my 30 candidate embeddings and return the top 3 closest matches so I can check for near-duplicate content."}],"resultDescription":"Returns the top-K most similar candidate vectors ranked by similarity score, including their IDs, scores, and associated metadata fields from the candidate list.","failureModes":["Wrong vector dimensionality (not 1536-d) causes rejection or incorrect results","Empty candidate_vectors array returns no results","top_k larger than candidate list returns fewer results than requested","Malformed float values in query_vector cause computation errors","Missing required query_vector field returns an error response"],"whenToPreferThis":"Choose this endpoint when you need fast, single-call vector similarity ranking over a bounded candidate set without maintaining a persistent index — ideal for on-the-fly semantic search, re-ranking, or nearest-neighbor lookup over a list you already have in memory. Prefer a persistent vector database service if you need to store and repeatedly query a large, growing index.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:38:18.261Z","isFirstParty":false,"canonicalSlug":"turboshop-ai-vector-similarity-search-73a42765"}