gg402 · Natural Language to ML Model

Served byx402 API Marketplace | Pay-per-call APIs with Crypto Indexed external

Create ML models from plain English descriptions with generated code and evaluation metrics.

What it does

Create ML models from plain English descriptions with generated code and evaluation metrics.

  • Generate predictive models from business requirements
  • Automate ML pipeline creation for data teams
  • Prototype models from stakeholder descriptions

Ideal buyer

ML automation agents and data science teams accelerating model development from requirements.

Use with AXON

Run this through your governed agent wallet.

  1. 01
    Bootstrap AXON once with npx @axon402/init.
  2. 02
    Use the AXON runtime MCP tools to search_x402_services or inspect_x402_offer for this service.
  3. 03
    Quote, test-buy, then run the governed paid fetch through AXON.

Send this

Prompt for your agent

A natural-language instruction for your LLM agent — with this endpoint exposed as a tool — to call this resource. Not sent to the endpoint; the endpoint consumes the JSON body below.

Pasting this prompt into a raw ChatGPT or unconfigured agent will notexecute the paid endpoint flow. Run it through an agent with the AXON runtime / MCP tools exposed (see “Use with AXON” above) so the 402 challenge, quote, and governed fetch are handled for you.

“Build a model to predict customer churn based on last purchase date and support tickets.”

Endpoint request body

The JSON payload your agent sends to the endpoint.

application/json
{
  "data_format": "csv with customer_id, last_purchase_date, ticket_count, churned",
  "description": "Predict customer churn using recency of last purchase and number of support tickets"
}

Advanced HTTP details

For integrators who need the raw protocol surface. Most agents should use AXON above instead of calling these directly.

curl fallback

curl https://gg402.vercel.app/nl_to_ml_model \
  -H "Content-Type: application/json" \
  -H "X-PAYMENT: [signed_payment_envelope]" \
  -d '{"data_format":"csv with customer_id, last_purchase_date, ticket_count, churned","description":"Predict customer churn using recency of last purchase and number of support tickets"}'

Payment & settlement details

Raw on-chain settlement parameters. AXON above handles these automatically through quote / test-buy / governed fetch.

baseexact
$0.010
per call
Pay-to address0x9257cd24721e3c06e9f7655b77c283bcd9652132
T/O: 60s asset 0x8335…2913

Price & network

Cheapest call$0.010
Networks
base

Trust & risk

Trust tier Indexed external
Risk flagsNo risks flagged
View JSON bundle

Indexed from facilitator discovery data

Last enriched:

More in AI / ML

Browse all →

Other resources in this category

Category proxy — we don't track live co-purchase signals yet.