SwarmZero provides a platform for developers to build, deploy, and monetize AI agents. It offers an Agent Hub marketplace where developers can create and customize AI agents, while users can discover and utilize these agents for various tasks. The platform supports multiple LLM models and provides tools for creating both individual agents and swarms of collaborative agents.

​
Setup

  1. Install Langtrace’s SDK and initialize the SDK in your code.
  2. Install SwarmZero’s SDK:
pip install swarmzero
  1. Use the langtrace SDK to capture traces from your SwarmZero app.

​
Configuration

  1. Create a .env file in your project directory and add your OpenAI API key:
OPENAI_API_KEY=your-api-key-here
  1. Create a configuration file (e.g., swarmzero_config.toml) for your SwarmZero agent:
[agent]
model = "gpt-3.5-turbo"
timeout = 15
environment = "dev"
  1. Initialize the SwarmZero agent with Langtrace:
from langtrace_python_sdk import langtrace
from swarmzero import Agent
from dotenv import load_dotenv

# Initialize Langtrace
langtrace.init(api_key=os.environ['LANGTRACE_API_KEY'])

# Load environment variables
load_dotenv()

# Create and run your agent
my_agent = Agent(
    name="my_agent",
    functions=[],
    instruction="your instructions for this agent's goal",
    config_path="./swarmzero_config.toml"
)
my_agent.run()

​
Advanced Features

​
Creating Agent Swarms

SwarmZero allows you to create swarms of collaborative agents:

from swarmzero.swarm import Swarm
from swarmzero.agent import Agent
from swarmzero.sdk_context import SDKContext

# Create individual agents
agent1 = Agent(name="Research Agent", instruction="Conduct research")
agent2 = Agent(name="Analysis Agent", instruction="Analyze data")

# Create swarm
swarm = Swarm(
    name="Research Team",
    description="Collaborative research agents",
    agents=[agent1, agent2]
)

​
Adding Retrievers

Enable semantic search and document analysis:

my_agent = Agent(
    name="retrieve-test",
    functions=[],
    retrieve=True,
    required_exts=['.md'],
    retrieval_tool='chroma'
)

For more detailed information about SwarmZero’s features and capabilities, visit their documentation.

SwarmZero provides a platform for developers to build, deploy, and monetize AI agents. It offers an Agent Hub marketplace where developers can create and customize AI agents, while users can discover and utilize these agents for various tasks. The platform supports multiple LLM models and provides tools for creating both individual agents and swarms of collaborative agents.

​
Setup

  1. Install Langtrace’s SDK and initialize the SDK in your code.
  2. Install SwarmZero’s SDK:
pip install swarmzero
  1. Use the langtrace SDK to capture traces from your SwarmZero app.

​
Configuration

  1. Create a .env file in your project directory and add your OpenAI API key:
OPENAI_API_KEY=your-api-key-here
  1. Create a configuration file (e.g., swarmzero_config.toml) for your SwarmZero agent:
[agent]
model = "gpt-3.5-turbo"
timeout = 15
environment = "dev"
  1. Initialize the SwarmZero agent with Langtrace:
from langtrace_python_sdk import langtrace
from swarmzero import Agent
from dotenv import load_dotenv

# Initialize Langtrace
langtrace.init(api_key=os.environ['LANGTRACE_API_KEY'])

# Load environment variables
load_dotenv()

# Create and run your agent
my_agent = Agent(
    name="my_agent",
    functions=[],
    instruction="your instructions for this agent's goal",
    config_path="./swarmzero_config.toml"
)
my_agent.run()

​
Advanced Features

​
Creating Agent Swarms

SwarmZero allows you to create swarms of collaborative agents:

from swarmzero.swarm import Swarm
from swarmzero.agent import Agent
from swarmzero.sdk_context import SDKContext

# Create individual agents
agent1 = Agent(name="Research Agent", instruction="Conduct research")
agent2 = Agent(name="Analysis Agent", instruction="Analyze data")

# Create swarm
swarm = Swarm(
    name="Research Team",
    description="Collaborative research agents",
    agents=[agent1, agent2]
)

​
Adding Retrievers

Enable semantic search and document analysis:

my_agent = Agent(
    name="retrieve-test",
    functions=[],
    retrieve=True,
    required_exts=['.md'],
    retrieval_tool='chroma'
)

For more detailed information about SwarmZero’s features and capabilities, visit their documentation.