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Building Your First Agent in Astreus

Berke (pzzaworks)Berke (pzzaworks)

December 1st, 2025

Building AI agents doesn't need to be complicated. With Astreus, you can create a working agent in just a few lines of code. This tutorial covers the fundamentals using the real Astreus API.

Quick Start

You can clone the complete example or start from scratch:

Bash
git clone https://github.com/astreus-ai/astreus cd your-first-agent npm install

Or install just the package:

Bash
npm install @astreus-ai/astreus

Environment Setup

Create a .env file with your configuration:

Env
OPENAI_API_KEY=sk-your-openai-api-key-here DB_URL=sqlite://./astreus.db

The database URL can point to SQLite for local development or PostgreSQL for production.

Creating Your First Agent

Here's the basic agent implementation:

TypeScript
import { Agent } from '@astreus-ai/astreus'; const agent = await Agent.create({ name: 'MyFirstAgent', model: 'gpt-4o', systemPrompt: 'You are a helpful assistant.' });

The Agent.create() method takes three core parameters: a name for identification, the LLM model to use, and a system prompt that defines the agent's behavior and personality.

Working with Tasks

Tasks provide structure for agent interactions. Create a task with a prompt, then execute it:

TypeScript
const task = await agent.createTask({ prompt: "Hello, introduce yourself" }); const result = await agent.executeTask(task.id); console.log(result.response);

The createTask() method generates a task object with an ID and status. The executeTask() method processes the task and returns the agent's response.

Running Your Agent

If you cloned the repository:

Bash
npm run dev

For a standalone script:

Bash
npx tsx index.ts

Core API Methods

Astreus provides three essential methods for basic agent operations:

  • Agent.create() - Creates a new agent instance with configuration
  • agent.createTask() - Generates a task with a prompt and optional metadata
  • agent.executeTask() - Executes a task by ID and returns the response

These methods form the foundation for building more complex agent systems.

Complete Example

Here's everything together:

TypeScript
import { Agent } from '@astreus-ai/astreus'; const agent = await Agent.create({ name: 'MyFirstAgent', model: 'gpt-4o', systemPrompt: 'You are a helpful assistant.' }); const task = await agent.createTask({ prompt: "Hello, introduce yourself" }); const result = await agent.executeTask(task.id); console.log(result.response);

This creates an agent, assigns it a task, and logs the response. The agent uses GPT-4 to process the prompt and generate an answer.

What's Next

This is just the beginning. The Astreus framework supports more advanced features like memory, knowledge bases, vision capabilities, and multi-agent systems. Start with this foundation and expand as your needs grow.

Source Code

The complete working example is available on GitHub: astreus-ai/your-first-agent

This experiment is written for Astreus v0.5.37. Please ensure you are using a compatible version.

Keep reading

  • Building Agents with Memory in Astreus

    Learn how to build AI agents with persistent memory using Astreus. Store conversation history and retrieve context across sessions.

  • Building Agents with Knowledge in Astreus

    Create AI agents that can search and retrieve information from knowledge bases using RAG. Learn how to integrate documents, enable semantic search, and build domain-specific agents.

  • Building Basic Sub-Agents in Astreus

    Learn how to create and coordinate multiple AI agents using Astreus. Build specialized agents that work together under a coordinator for complex task delegation.