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dev-5090 Text Embedding API
x402
dev-5090 Text Embedding API is a paid API for AI agents from over-arabia-specifically-luxury.trycloudflare.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-10).
Generates 768-dimensional text embeddings for single strings or batches of strings
Price / call$0.005
Success—
StatusUnknown
How this service works
Text embeddings (768-dim). Send {"input": "text"} or {"input": ["a","b"]}.
Output
Returns an object with an array of 768-dimensional float vectors (one per input string), along with token usage statistics. Each embedding captures the semantic meaning of the input text in a dense numerical representation suitable for similarity search, clustering, or downstream ML tasks.
Example use cases
Semantic search index population
“Embed all these product descriptions for me so I can store them in my Pinecone index for semantic search: ['Wireless noise-cancelling headphones', 'Bluetooth portable speaker', 'USB-C charging cable'].”
Sentence similarity comparison
“I need to compare how similar these two sentences are — can you get embeddings for 'machine learning is transforming healthcare' and 'AI is revolutionizing medicine' so I can compute cosine similarity?”
RAG document chunking pipeline
“Vectorize this paragraph for me so I can add it to my retrieval-augmented generation knowledge base: 'Photosynthesis is the process by which plants convert sunlight into chemical energy stored as glucose.'”
Technical details
Endpoint
POSThttps://over-arabia-specifically-luxury.trycloudflare.com/v1/embed?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, affordable 768-dimensional text embeddings without a commercial API account. It is well-suited for prototyping semantic search pipelines, populating vector databases, or batch-embedding small corpora at low cost ($0.005/call). Prefer it over OpenAI or Cohere embedding APIs when you want a pay-per-call x402 micropayment model with no subscription required. The 768-dim output is compatible with many standard vector stores and similarity libraries.
Side effects
- Empty input string returns an error or zero vector
- Extremely long inputs may be truncated or rejected
- Batch inputs exceeding token limits may fail
- Service unavailability due to ephemeral Cloudflare tunnel going offline
- Malformed JSON body returns a 400 error
- Rate limiting or quota exhaustion from the x402 payment layer
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| usage | object | |
| choices | array |
Tags
x402
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