# My Actor 18 (`princes1obama/my-actor-18`) Actor

- **URL**: https://apify.com/princes1obama/my-actor-18.md
- **Developed by:** [Mubarak Obama](https://apify.com/princes1obama) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### PydanticAI template

Start a new [AI agent](https://blog.apify.com/what-are-ai-agents/) based project in Python with our PydanticAI project template. It provides a basic structure for the [Actor](https://apify.com/actors) using the [Apify SDK](https://docs.apify.com/sdk/python/) and [PydanticAI](https://ai.pydantic.dev/), and allows you to add your own functionality with minimal setup.

### How it works

Insert your own code to `async with Actor:` block. You can use the [Apify SDK](https://docs.apify.com/sdk/python/) with any other Python library. Add or modify the agent and tools in [`my_actor/agents.py`](my_actor/agents.py).

### LLM provider

The agent talks to its LLM through the [Apify OpenRouter proxy](https://apify.com/apify/openrouter) — an OpenAI-compatible endpoint at `https://openrouter.apify.actor/api/v1` that fronts the full [OpenRouter](https://openrouter.ai) model catalog. Token usage is billed against the user's Apify account (pay-per-event), so **no `OPENAI_API_KEY` or any other provider API key is required**. The Actor authenticates with the proxy using the `APIFY_TOKEN` that the platform injects into every run automatically.

If you'd rather call OpenAI / Anthropic / etc. directly with your own key, swap the `OpenAIProvider` configuration in `my_actor/agents.py` — see the [PydanticAI OpenAI docs](https://ai.pydantic.dev/models/openai/).

### Getting started

For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-locally). To run the Actor use the following command:

```bash
apify run
```

### Deploy to Apify

#### Connect Git repository to Apify

If you've created a Git repository for the project, you can connect to Apify:

1. Go to [Actor creation page](https://console.apify.com/actors/new)
2. Click on **Link Git Repository** button

#### Push project on your local machine to Apify

You can also deploy the project from your local machine to the Apify platform without the need for the Git repository.

1. Log in to Apify. You will need to provide your [Apify API Token](https://console.apify.com/account/integrations) to complete this action.

   ```bash
   apify login
   ```

2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under [Actors -> My Actors](https://console.apify.com/actors?tab=my).

   ```bash
   apify push
   ```

### Pay Per Event

This template uses the [Pay Per Event (PPE)](https://docs.apify.com/platform/actors/publishing/monetize#pay-per-event-pricing-model) 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:

```json
[
    {
        "task-completed": {
            "eventTitle": "Task completed",
            "eventDescription": "Flat fee for completing the task.",
            "eventPriceUsd": 0.01
        }
    }
]
```

In the Actor, trigger the event with:

```python
await Actor.charge(event_name='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 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](.actor/pay_per_event.json).

No provider API key (e.g. `OPENAI_API_KEY`) needs to be configured — LLM costs are billed through the Apify OpenRouter proxy to the user running the Actor.

### Resources

To learn more about Apify, Actors and PydanticAI take a look at the following resources:

- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)
- [AI agent architecture](https://blog.apify.com/ai-agent-architecture)
- [What are AI agents](https://blog.apify.com/what-are-ai-agents/)
- [How to build and monetize an AI agent on Apify](https://blog.apify.com/how-to-build-an-ai-agent/)
- [PydanticAI documentation](https://ai.pydantic.dev/)
- [PydanticAI on GitHub](https://github.com/pydantic/pydantic-ai)

### Getting started

For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-at-apify-console). In short, you will:

1. Build the Actor
2. Run the Actor

### Pull the Actor for local development

If you would like to develop locally, you can pull the existing Actor from Apify console using Apify CLI:

1. Install `apify-cli`

   **Using Homebrew**

   ```bash
   brew install apify-cli
   ```

   **Using NPM**

   ```bash
   npm -g install apify-cli
   ```

2. Pull the Actor by its unique `<ActorId>`, which is one of the following:

   - unique name of the Actor to pull (e.g. "apify/hello-world")
   - or ID of the Actor to pull (e.g. "E2jjCZBezvAZnX8Rb")

   You can find both by clicking on the Actor title at the top of the page, which will open a modal containing both Actor unique name and Actor ID.

   This command will copy the Actor into the current directory on your local machine.

   ```bash
   apify pull <ActorId>
   ```

### Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

- [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js)
- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)

# Actor input Schema

## `jokeTopic` (type: `string`):

The topic about which the AI agent will tell the joke about.

## `modelName` (type: `string`):

Model ID routed through the Apify OpenRouter proxy (https://apify.com/apify/openrouter). Tokens are charged automatically to your Apify account, so no provider API key is needed.

## Actor input object example

```json
{
  "jokeTopic": "Bad weather.",
  "modelName": "deepseek/deepseek-v4-flash"
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "jokeTopic": "Bad weather.",
    "modelName": "deepseek/deepseek-v4-flash"
};

// Run the Actor and wait for it to finish
const run = await client.actor("princes1obama/my-actor-18").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "jokeTopic": "Bad weather.",
    "modelName": "deepseek/deepseek-v4-flash",
}

# Run the Actor and wait for it to finish
run = client.actor("princes1obama/my-actor-18").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "jokeTopic": "Bad weather.",
  "modelName": "deepseek/deepseek-v4-flash"
}' |
apify call princes1obama/my-actor-18 --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,princes1obama/my-actor-18"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/3LpYi21nfbYfNf8Bi/builds/Agf3Aqs6p2FPHjTz0/openapi.json