meraGPT

overview

meraGPT API

meraGPT serves small models trained for a single job each, over an OpenAI-compatible HTTP API. Usage is metered per token against prepaid USD credit. There is no subscription and no seat count.

The base URL is https://meragpt.com/v1. One model is available today: Restyler 1 (text-restyler-1).

Quickstart

Three steps, about two minutes. You can skip straight to step three with the playground, which needs no account.

1. Add credit

Sign in with Google and add credit from the dashboard. The minimum is $10. It is a USD balance, not a token bundle, what you see is what is left.

2. Create a key

On the keys page, name a key and optionally restrict which models it may call and cap what it may spend. The secret is shown once, at creation. We store only a SHA-256 hash, so it cannot be shown again by us or by anyone who reaches our database.

3. Make a request

The task-native endpoint takes a whole document and handles splitting it into the paragraph-sized units the model was trained on:

curl https://meragpt.com/v1/restyle \
  -H "Authorization: Bearer $MERAGPT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-restyler-1",
    "text": "The utilization of our platform facilitates the optimization of workflow efficiency across organizational boundaries."
  }'

Or point an existing OpenAI client at the same base URL and change the model name:

from openai import OpenAI

client = OpenAI(
    api_key=os.environ["MERAGPT_API_KEY"],
    base_url="https://meragpt.com/v1",
)

resp = client.chat.completions.create(
    model="text-restyler-1",
    messages=[{"role": "user", "content": draft}],
)
print(resp.choices[0].message.content)

Which endpoint to use

Prefer /v1/restyle. The Restyler rewrites one paragraph at a time, and that endpoint splits your document, skips what should not be rewritten, reassembles the result with your formatting intact, and tells you per block what it did.

/v1/chat/completions exists so existing OpenAI code works unchanged. It does the same splitting internally, but the chat envelope cannot express the per-block detail, and sampling parameters are accepted and ignored because decoding is fixed.

Where to go next