Quick Start Guide

Build your first agentic AI solution with Kodey.ai in minutes

This guide will walk you through creating, configuring, and deploying your first AI agent on the Kodey.ai platform. By the end, you'll have a functioning agent that can be accessed via API, WebSocket, or embedded in a web application.

Prerequisites

Before you begin, ensure you have:

  • Node.js v18 or higher installed
  • A Kodey.ai account (sign up at developer.kodey.ai if you don't have one)
  • Your Kodey.ai API key (available from your developer dashboard)

Step 1: Install the Kodey CLI

The Kodey CLI is the fastest way to get started. Open your terminal and run:

npm install -g @kodey/cli

Verify the installation was successful:

kodey --version

Step 2: Create a New Agent Project

Initialize a new agent project:

kodey init my-first-agent
cd my-first-agent

This creates a new directory with all the necessary files for your agent.

Step 3: Configure Your Agent

Open the generated config/agent_config.yaml file and customize your agent:

agent:
  name: "my_assistant"
  description: "A helpful assistant that can answer questions and perform tasks"
  type: "assistant"
  
  # Configure which tools your agent can use
  tools:
    - name: "web_search"
      enabled: true
    
    - name: "calculator"
      enabled: true
  
  # Choose your preferred language model
  model:
    provider: "anthropic"
    model_name: "claude-3-sonnet"

Then set up your API keys by creating a .env file:

KODEY_API_KEY=your_kodey_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key

Step 4: Add a Custom Tool (Optional)

Create a custom tool to extend your agent's capabilities:

  1. Create a new file in the tools directory:
mkdir -p tools/custom
touch tools/custom/weather_tool.py
  1. Implement your tool:
# tools/custom/weather_tool.py
from kodey.tools import BaseTool
import requests

class WeatherTool(BaseTool):
    """Tool for fetching current weather information."""
    
    name = "weather"
    description = "Gets the current weather for a given location"
    
    def _run(self, location: str) -> str:
        """Get weather for the specified location."""
        # Example implementation - replace with actual API call
        api_key = self.get_env_variable("WEATHER_API_KEY")
        response = requests.get(
            f"https://api.weatherapi.com/v1/current.json?key={api_key}&q={location}"
        )
        data = response.json()
        return f"Current weather in {location}: {data['current']['temp_c']}°C, {data['current']['condition']['text']}"
  1. Register your tool in the agent config:
tools:
  - name: "weather"
    enabled: true
    config:
      api_key: "${WEATHER_API_KEY}"
  1. Add the required API key to your .env file:
WEATHER_API_KEY=your_weather_api_key

Step 5: Test Your Agent Locally

Run your agent in development mode to test it:

kodey dev

This starts a local development server where you can interact with your agent through a test interface. Try sending messages like:

  • "What's the weather in New York?"
  • "Calculate 15% of 85.75"
  • "Tell me about machine learning"

Step 6: Deploy Your Agent

When you're satisfied with your agent's functionality, deploy it to the Kodey.ai platform:

kodey deploy

After a successful deployment, you'll receive:

  • A unique agent URL
  • API endpoint information
  • WebSocket connection details
  • HTML code snippet for web integration

Step 7: Integrate Your Agent

REST API Integration

To use your agent via the REST API:

// JavaScript example
async function callAgent(message) {
  const response = await fetch('https://api.kodey.ai/agents/my-first-agent', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'Authorization': 'Bearer YOUR_API_KEY'
    },
    body: JSON.stringify({
      messages: [{ role: 'user', content: message }]
    })
  });
  
  return response.json();
}

// Usage
callAgent("What's the weather in London?").then(console.log);

Web Integration

To embed your agent in a web application, use the provided HTML snippet:

<div id="kodey-agent"></div>
<script src="https://cdn.kodey.ai/embed.js"></script>
<script>
  Kodey.init({
    agentId: 'my-first-agent',
    targetElementId: 'kodey-agent',
    apiKey: 'YOUR_PUBLIC_API_KEY'
  });
</script>

Next Steps

Congratulations! You've built and deployed your first Kodey.ai agent. Here are some next steps to enhance your agent:

  1. Add More Tools: Explore the tools/ directory to add more capabilities
  2. Customize Behavior: Adjust your agent's personality and responses in the config
  3. Set Up Workflows: Create complex sequences using the workflow agent type
  4. Connect Data Sources: Integrate databases or APIs using the data connectors

For more detailed information, check out:

Happy building!