Mastra social media agent

1// Apify SDK - toolkit for building Apify Actors (Read more at https://docs.apify.com/sdk/js/)
2import { Actor, log } from 'apify';
3
4import { createSocialMediaAgent } from './agents.js';
5
6// this is ESM project, and as such, it requires you to specify extensions in your relative imports
7// read more about this here: https://nodejs.org/docs/latest-v18.x/api/esm.html#mandatory-file-extensions
8// note that we need to use `.js` even when inside TS files
9// import { router } from './routes.js';
10
11// Actor input schema
12interface Input {
13    query: string;
14    modelName: string;
15}
16
17// The init() call configures the Actor to correctly work with the Apify-provided environment - mainly the storage infrastructure. It is necessary that every Actor performs an init() call.
18await Actor.init();
19
20/**
21 * Actor code
22 */
23
24// Handle input
25const {
26    // The query default value is provided only for template testing purposes.
27    // You can remove it.
28    query,
29    modelName,
30} = (await Actor.getInput()) as Input;
31if (!query) {
32    throw new Error('An agent query is required.');
33}
34
35// Create the social media agent with tools
36const agent = createSocialMediaAgent(modelName);
37
38log.info(`Querying the agent with the following query: ${query}`);
39
40// Query the agent and get the response
41const response = await agent.generate([{ role: 'user', content: query }]);
42
43log.info(`Agent response: ${response.text}`);
44
45// Charge for the task completion
46await Actor.charge({ eventName: 'task-completed' });
47
48// Push results into the dataset
49await Actor.pushData({
50    query,
51    response: response.text,
52});
53
54// Gracefully exit the Actor process. It's recommended to quit all Actors with an exit()
55await Actor.exit();

A template for Mastra  projects in TypeScript for building AI agents with Apify Actors . The template provides a basic structure and an example agent  that calls Actors  as tools in a workflow.

An agent  is created and given a set of tools to accomplish a task. The agent receives a query from the user and decides which tools to use and in what order to complete the task. In this case, the agent is provided with an Instagram Scraper Actor  to scrape Instagram profile posts. The agent produces textual output, which is saved to a dataset.

Add or modify the agent tools in the src/tools.ts file, and make sure to include new tools in the agent tools list in src/agents.ts. Additionally, you can update the agent prompts in src/agents.ts. For more information, refer to the Mastra agent documentation  and the Mastra tools documentation .

This template uses the Pay Per Event (PPE)  monetization model, which provides flexible pricing based on defined events.

To charge users, define events in JSON format and save them on the Apify platform. Here is an example schema with the task-completed event:

[
    {
        "task-completed": {
            "eventTitle": "Task completed",
            "eventDescription": "Cost per query answered.",
            "eventPriceUsd": 0.1
        }
    }
]

In the Actor, trigger the event with:

await Actor.charge({ eventName: 'task-completed' });

This approach allows you to programmatically charge users directly from your Actor, covering the costs of execution and related services, such as LLM input/output tokens.

To set up the PPE model for this Actor:

• Configure the OpenAI API key environment variable: provide your OpenAI API key to the OPENAI_API_KEY in the Actor's Environment variables.
• Configure Pay Per Event: establish the Pay Per Event pricing schema in the Actor's Monetization settings. First, set the Pricing model to Pay per event and add the schema. An example schema can be found in pay_per_event.json.

• Apify SDK  for JavaScript - a toolkit for building Apify Actors  and scrapers in JavaScript
• Input schema  - define and easily validate a schema for your Actor's input
• Dataset  - store structured data where each object stored has the same attributes
• Key-value store  - store any kind of data, such as JSON documents, images, or text files

• What are AI agents? 
• TypeScript tutorials in Academy 
• Apify SDK documentation 
• Mastra documentation 
• Integration with Make, GitHub, Zapier, Google Drive, and other apps