{"uid":"cap_x9R5iSnji6B4IZhIYqvdp","slug":"perplexity-embeddings-via-locus-x402-e3a77b4f","name":"Perplexity Embeddings via Locus x402","description":"AI-powered search — Sonar chat with real-time web grounding, web search, and embeddings.","url":"https://perplexity.x402.paywithlocus.com/perplexity/embed","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"input":{"anyOf":[{"type":"string"},{"type":"array","items":{"type":"string"}}]},"model":{"type":"string"}}},"responseSchema":{"type":"json","example":{"data":{},"payment":{"scheme":"exact","settledUsdc":"0.001000","authorizedMaxUsdc":"0.001000"},"request":{"id":"00000000-0000-4000-8000-000000000000","statusUrl":"/requests/00000000-0000-4000-8000-000000000000"},"success":true}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.001","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","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":"$0.001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_NhI4ZoC0tSGTMCVfcnuG3","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.001","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Generates vector embeddings for text using Perplexity's pplx-embed models, paid per-call via x402 micropayments.","exampleAgentPrompt":"Can you embed this text using the Perplexity pplx-embed-v1-4b model: 'The quick brown fox jumps over the lazy dog' — I need the vector representation for a semantic search index.","exampleUseCases":[{"title":"RAG pipeline document indexing","prompt":"Take these three product description chunks and embed them using Perplexity's pplx-embed-v1-4b model so I can store them in my vector database for retrieval."},{"title":"Semantic similarity scoring","prompt":"Embed these two sentences using pplx-embed-v1-0.6b so I can compare how semantically similar they are: 'climate change impacts agriculture' and 'global warming affects crop yields'."},{"title":"User query vectorization","prompt":"I need to vectorize this user search query — 'best running shoes for flat feet' — using pplx-embed-v1-4b so I can do a nearest-neighbor lookup against my product catalog embeddings."}],"resultDescription":"Returns a JSON object containing the embedding data (dense vector representations of the input text), a payment record showing 0.001 USDC settled, and a request ID with a status URL for tracking. The embedding vectors can be used directly in vector databases, similarity search, or downstream ML tasks.","failureModes":["Invalid model name returns an error — must be 'pplx-embed-v1-0.6b' or 'pplx-embed-v1-4b'","Empty or missing input array causes a validation error","Insufficient USDC balance or failed x402 payment results in request rejection","Input text exceeding model token limits may be truncated or rejected","Network timeout on large batches of strings"],"whenToPreferThis":"Choose this endpoint when you need pay-per-use text embeddings without a subscription commitment, especially in agentic workflows that require micropayment-native infrastructure. Prefer this over OpenAI or Cohere embedding APIs when you want x402-compatible billing or when you specifically want Perplexity's pplx-embed models for their semantic quality characteristics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-13T12:31:37.719Z","isFirstParty":false}