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GEDX402 Large Text Embedding API
x402
GEDX402 Large Text Embedding API is a paid API for AI agents from embed.gedx402.com, paid per call via x402, $0.018/call, status unknown (last checked 2026-09-15).
Generates large-dimension vector embeddings for text strings using Workers AI, payable with USDC via x402 protocol — no API keys required.
Price / call$0.018
Success—
StatusUnknown
How this service works
Generate text embeddings with BGE Large EN V1.5 (@cf/baai/bge-large-en-v1.5). POST text or texts[] for semantic search, RAG retrieval, and clustering; billed by input character volume.
Output
A JSON object containing a `data` array where each item has an `index` (integer position) and `embedding` (array of floats representing the vector). For a single text input, returns one embedding object; for batch inputs, returns one embedding object per text string.
Example use cases
Semantic search across customer support tickets
“I need to embed our entire support ticket archive into vectors so our agent can find the most similar past tickets when a new customer question comes in. Can you convert all the ticket summaries to embeddings using the GEDX402 service and pay from our USDC wallet?”
Document similarity matching for legal contracts
“We're comparing dozens of vendor contracts to find ones with similar terms and clauses. Please embed each contract section as vectors so we can identify which ones are semantically closest to our template agreement. Use GEDX402 and charge our Polygon account.”
Query embedding for RAG knowledge base retrieval
“When users ask questions, embed their queries into vectors so our system can pull the most relevant documents from our knowledge base. Set up the embeddings pipeline with GEDX402 Workers AI and handle payments in USDC on Arbitrum.”
Technical details
Endpoint
GEThttps://embed.gedx402.com/v1/embed/largeWhen to prefer
Choose this endpoint when you need text embeddings without managing API keys, want to pay per-call with USDC cryptocurrency on chains like Base, Polygon, Arbitrum, World, or Solana, and need large-dimension embeddings suitable for high-quality semantic search or RAG pipelines. Prefer over OpenAI or Cohere embeddings when operating in a crypto-native or x402 payment-gated environment.
Side effects
- Payment not received or insufficient USDC balance — returns 402 Payment Required
- Text input missing or empty — returns 400 Bad Request
- Text exceeds model token limit — may return 400 or truncation
- Batch array too large — may hit rate or size limits
- Network or Workers AI upstream failure — returns 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | |
| texts | array |
Tags
x402
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