Quick Start

In this quick start, you'll learn the key concepts and experience the AgentifyMe workflow. It should only take about 5 minutes to complete and by the end you'll have your first agentic workflow up and running on the cloud.

Running BotifyMe in the local environment

AgentifyMe provides a rich development experience that allows you to quickly iterate on Workflows and Tasks, even before they've been deployed. To manage code for workflows and tasks, we recommend using the AgentifyMe CLI to start the local development server.

BotifyMe relies on Docker containers to manage local development environments. Ensure you install and test Docker on your machine as a first step:

To create a new project, navigate to the desired directory and run:

botifyme init

This command generates a botifyme.yml configuration file in your project directory. You can safely commit this directory to your version control system. For more details on the configuration schema, visit the Configuration Schema Documentation.

To launch the BotifyMe local environment, execute:

botifyme dev

This command reads the configuration file, builds sandbox environments, and constructs the required Docker images. Note that downloading Docker images depends on your internet bandwidth and may take longer during the initial setup.

To shut down the local BotifyMe environment when your work is complete, use:

botifyme dev down

Taxonomy includes a documentation site built using Contentlayer and MDX.

Features

It comes with the following features out of the box:

  1. Write content using MDX.
  2. Transform and validate content using Contentlayer.
  3. MDX components such as
  4. Support for table of contents.
  5. Custom navigation with prev and next pager.

How is it built

Click on a section below to learn how the documentation site built.

Contentlayer

Learn how to use MDX with Contentlayer.

Components

Using React components in Mardown.

View
Code Blocks

Beautiful code blocks with syntax highlighting.

View
Style Guide

View a sample page with all the styles.

View

Create speech

Generates audio from the input text.

Example request

Request body

file

filerequired
The language of the input audio. Supplying the input language in ISO-639-1 format will improve accuracy and latency.

model

stringoptional
The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.
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