Endercom CLI

A command-line interface for deploying and managing AI agents on AWS Lambda using the Endercom framework.

Installation

pip install endercom-cli

Prerequisites

Before you begin, ensure you have:

1. An AWS Account: You'll need credentials to deploy resources.
2. AWS CLI Configured: Run aws login to set your credentials and default region.

   brew install awscli
   aws login
   

3. AWS SAM CLI: Required for building and deploying the serverless stack.

   brew install aws-sam-cli
   

Quick Start

1. Initialize an Agent Project

Create a new agent project structure.

endercom init <agent-name>

This scaffolds a directory with:

• agent.py: Your agent logic (where you write code)
• app.py: Server entry point and wrapper
• template.yaml: AWS SAM infrastructure definition
• requirements.txt: Python dependencies
• .endercom/agent.yaml: CLI configuration

2. Configure Environment (Optional)

If your agent needs API keys (e.g., OPENAI_API_KEY), add them to the secrets manager.

cd <agent-name>
endercom secrets set OPENAI_API_KEY "sk-..."

3. Deploy

Build and deploy your agent to AWS.

endercom deploy

The CLI will:

• Check your code for undeclared environment variables.
• Sync your configuration to the SAM template.
• Build the agent using sam build.
• Deploy using sam deploy.

Commands

Configuration

The source of truth for your agent's configuration is .endercom/agent.yaml.

name: my-agent
runtime: python3.12
region: us-east-1
memory: 1024
timeout: 30
env:
  MY_PUBLIC_VAR: "production"
secrets:
  - OPENAI_API_KEY

• env: Standard environment variables injected at deployment.
• secrets: List of keys to resolve securely from AWS Secrets Manager.