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Animica Text Embedding API
x402
Animica Text Embedding API is a paid API for AI agents from animica.dev, paid per call via x402, $0.001796/call, status unknown (last checked 2026-09-15).
Generates dense vector embeddings for up to 256 texts in a single call, returning unit-normalized vectors with dimension and character count metadata.
Price / call$0.001796
Success—
StatusUnknown
How this service works
Embed up to 256 texts in ONE call with all-MiniLM-L6-v2 (384-dimensional, normalised for cosine similarity), up to 8192 characters each. Sold as a batch on purpose: a single settlement costs real gas, so a per-string price would be almost entirely payment overhead — one call, many vectors, is the only honest shape for this. This is a small fast local sentence-transformer, not a frontier embedding model; the model id rides on every response so a future change is visible rather than silent.
Output
A JSON object containing the embedding model name, vector dimensionality, count of embedded texts, a 2D array of float vectors (one per input text, in request order), total character count across all inputs, and per-text character counts. Vectors are unit-normalized by default for direct cosine similarity use.
Example use cases
RAG pipeline document chunking
“I have 50 text chunks from my knowledge base docs — can you embed all of them into vectors so I can load them into my Pinecone index for retrieval-augmented generation?”
Semantic search query vectorization
“Embed this user search query so I can find the nearest matching products in my vector store: 'comfortable shoes for long walks in the city'.”
Customer review clustering
“I have 200 short customer reviews — embed all of them into vectors so I can run k-means clustering and group them by topic automatically.”
Technical details
Endpoint
POSThttps://animica.dev/x402/embedWhen to prefer
Choose this endpoint when you need batch text embeddings (up to 256 at once) via a pay-per-call x402 micropayment model without managing an OpenAI API key. It is ideal for AI agents with crypto wallets that need on-demand embeddings for semantic search, RAG pipelines, or clustering tasks at low per-call cost ($0.005 USDC).
Side effects
- Exceeding 256 texts in a single request returns a validation error
- Empty texts array returns an error
- Payment failure via x402 protocol blocks the request
- Very long individual strings may cause timeout or character-limit errors
- Malformed JSON body returns a 400 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| texts | array | 1..256 strings |
| normalize | boolean | vectors are already unit-normalised; set false only if you want them raw (default true) |
Output
Schema · Response
{
"type": "json"
}Tags
x402
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