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Client Setup & Basic Usage

This example demonstrates how to set up the Swarms API client and perform basic operations including health checks, model listing, and rate limit monitoring.

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What This Example Shows

  • Setting up the Swarms API client
  • Checking API health status
  • Listing available models
  • Monitoring rate limits
  • Accessing swarm logs and availability

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Installation

pip3 install -U swarms-client

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Get Your Swarms API Key

  1. Visit https://swarms.world/platform/api-keys
  2. Create an account or sign in
  3. Generate a new API key
  4. Store it securely in your environment variables

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Code

import os
import json
from dotenv import load_dotenv
from swarms_client import SwarmsClient

# Load environment variables
load_dotenv()

# Initialize the client
client = SwarmsClient(api_key=os.getenv("SWARMS_API_KEY"))

# Check available models
print("Available Models:")
print(json.dumps(client.models.list_available(), indent=4))

# Check API health
print("\nAPI Health:")
print(json.dumps(client.health.check(), indent=4))

# Get swarm logs
print("\nSwarm Logs:")
print(json.dumps(client.swarms.get_logs(), indent=4))

# Check rate limits
print("\nRate Limits:")
print(json.dumps(client.client.rate.get_limits(), indent=4))

# Check swarm availability
print("\nSwarm Availability:")
print(json.dumps(client.swarms.check_available(), indent=4))

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Expected Output

The script will output JSON responses showing:
  • List of available AI models
  • API health status
  • Recent swarm execution logs
  • Current rate limit usage
  • Swarm service availability

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Environment Setup

Create a .env file in your project directory: 
SWARMS_API_KEY=your_api_key_here

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Next Steps

After running this example, you’ll be ready to:
  • Create single agents for specific tasks
  • Build multi-agent swarms for complex workflows
  • Implement batch processing for multiple requests
  • Monitor and manage your API usage