# Create embedding — OpenAI ChatGPT

Botize method — `chatgpt.create_embedding` (action).

Given a text, create the corresponding vector

This is an action: it runs as a step of a task. Several can be chained.

## Fields you set

The field's internal name, its type and the values it accepts. These fields accept `{{...}}` tags from earlier steps.

- `mb_switch` *(boolean)* — Rules
- `input` *(string)* — Text
- `model` *(string)* — Model

It also accepts repeatable field groups, with these prefixes: `mb_filters_*`. These are composite components (buttons, filters, keyboards); the trailing number is set by the user as they are added.

## Output variables

Data this step makes available. Reference them in later steps with the double-brace tag.

- `{{embedding_url}}` *(text)* — Embedding URL. The URL where the generated embedding can be accessed.
e.g. chatgpt_vector.json
- `{{total_tokens}}` *(int)* — Total Tokens. The total number of tokens used in the embedding process.
e.g. 2

## Account

Needs a connected OpenAI ChatGPT account in Botize: https://botize.com/en/app/chatgpt/authenticate

## This app

Every trigger and action for OpenAI ChatGPT: https://botize.com/en/app/chatgpt.md

## How to build this

An AI assistant (Claude, ChatGPT, Cursor…) can create and edit these tasks in the user's account through the Botize MCP connector, included in every plan:

    https://webhook.botize.es/mcp

- Connection guide: https://botize.com/en/mcp
- Agent map: https://botize.com/llms.txt
- New account: https://botize.com/en/join (500 free operations, no card)

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Machine-readable summary for AI assistants. Human version: https://botize.com/en/method/chatgpt/create_embedding