# Embeddings

> Turn text into vectors with POST /v1/embeddings, paid with a key or per request with x402.

Section: Developers. Web page: https://docs.katara.com/developers/embeddings/

`POST https://api.katara.com/v1/embeddings` takes the OpenAI embeddings request and returns one vector per input. The model is `katara/bge-base-en-v1.5@1`, an English model with 768 dimensions.

```sh
curl https://api.katara.com/v1/embeddings \
  -H "Authorization: Bearer $KATARA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"katara/bge-base-en-v1.5@1","input":["The first passage.","The second passage."]}'
```

With the OpenAI client, `client.embeddings.create(model="katara/bge-base-en-v1.5@1", input=[...])` works unchanged.

## What a request takes

| Field | |
|---|---|
| `model` | `katara/bge-base-en-v1.5@1`. |
| `input` | A string, or a list of up to 100 strings. Each input is read up to 512 tokens. Token arrays are not accepted. |
| `encoding_format` | `float` (the default) or `base64`, little-endian 32-bit floats as OpenAI sends them. |
| `dimensions` | Only `768`. The model cannot shorten its vectors. |
| `user` | Accepted and not passed on. |

Any other field is refused with `400` and code `unsupported_parameter`. `/v1/models` lists the model with its `dimensions`, `max_input_tokens`, `max_inputs` and price.

## The reply

```json
{
  "object": "list",
  "data": [{ "object": "embedding", "index": 0, "embedding": [0.0123, -0.0456] }],
  "model": "katara/bge-base-en-v1.5@1",
  "usage": { "prompt_tokens": 9, "total_tokens": 9 },
  "katara": { "cost_usdc": "0.000001", "provider": "managed", "fallback": true, "served": { "model": "katara/bge-base-en-v1.5@1", "managed": true } }
}
```

`usage.prompt_tokens` is what you are charged for: the count the model reports, or, when it reports none, one token for every four bytes of an input plus two per input, never more than 512 per input.

## Paying

- A key that pays with USDC is charged per million input tokens at the price `/v1/models` lists, settled like a chat reply.
- A key that pays with Account Credits is charged in credits; `katara.cost_usd` carries the charge.
- Without a key, the request is paid with [x402](https://docs.katara.com/developers/x402.txt): the same quote, schemes, 0.025 USDC minimum and settlement as a chat completion. The quote assumes every input is as long as the model takes, and the settlement charges the tokens counted.

Embeddings are served by Katara's own models only, never by Katara Community, whatever pays. A failure before the vectors come back is not charged.