docs/swarms/structs/auto_swarm.md

AutoSwarm

The AutoSwarm class represents a swarm of agents that can be created and managed automatically. This class leverages the AutoSwarmRouter to route tasks to appropriate swarms and supports custom preprocessing, routing, and postprocessing of tasks. It is designed to handle complex workflows efficiently.

Key Concepts

• Swarm: A group of agents working together to complete tasks.
• Routing: Directing tasks to the appropriate swarm based on specific criteria.
• Preprocessing and Postprocessing: Customizable functions to handle tasks before and after routing.
• Event Loop: Managing the execution of tasks in a loop.

Attributes

Arguments

Argument	Type	Default	Description
name	Optional[str]	None	The name of the swarm.
description	Optional[str]	None	The description of the swarm.
verbose	bool	False	Whether to enable verbose mode.
custom_params	Optional[Dict[str, Any]]	None	Custom parameters for the swarm.
custom_preprocess	Optional[Callable]	None	Custom preprocessing function for tasks.
custom_postprocess	Optional[Callable]	None	Custom postprocessing function for task results.
custom_router	Optional[Callable]	None	Custom routing function for tasks.
max_loops	int	1	The maximum number of loops to run the workflow.

Attributes

Attribute	Type	Description
name	Optional[str]	The name of the swarm.
description	Optional[str]	The description of the swarm.
verbose	bool	Whether to enable verbose mode.
custom_params	Optional[Dict[str, Any]]	Custom parameters for the swarm.
custom_preprocess	Optional[Callable]	Custom preprocessing function for tasks.
custom_postprocess	Optional[Callable]	Custom postprocessing function for task results.
custom_router	Optional[Callable]	Custom routing function for tasks.
max_loops	int	The maximum number of loops to run the workflow.
router	AutoSwarmRouter	The router for managing task routing.

Methods

init_logging

Initializes logging for the AutoSwarm.

Examples:

swarm = AutoSwarm(name="example_swarm", verbose=True)
swarm.init_logging()

run

Runs the swarm simulation.

Arguments:

Parameter	Type	Default	Description
task	str	None	The task to be executed.
*args			Additional arguments.
**kwargs			Additional keyword arguments.

Returns:

Return Type	Description
Any	The result of the executed task.

Raises:

• Exception: If any error occurs during task execution.

Examples:

swarm = AutoSwarm(name="example_swarm", max_loops=3)
result = swarm.run(task="example_task")
print(result)

list_all_swarms

Lists all available swarms and their descriptions.

Examples:

swarm = AutoSwarm(name="example_swarm", max_loops=3)
swarm.list_all_swarms()
# Output:
# INFO: Swarm Name: swarm1 || Swarm Description: Description of swarm1
# INFO: Swarm Name: swarm2 || Swarm Description: Description of swarm2

Additional Examples

Example 1: Custom Preprocessing and Postprocessing

def custom_preprocess(task, *args, **kwargs):
    # Custom preprocessing logic
    task = task.upper()
    return task, args, kwargs

def custom_postprocess(result):
    # Custom postprocessing logic
    return result.lower()

swarm = AutoSwarm(
    name="example_swarm",
    custom_preprocess=custom_preprocess,
    custom_postprocess=custom_postprocess,
    max_loops=3
)

# Running a task with custom preprocessing and postprocessing
result = swarm.run(task="example_task")
print(result)  # Output will be the processed result

Example 2: Custom Router Function

def custom_router(swarm, task, *args, **kwargs):
    # Custom routing logic
    if "specific" in task:
        return swarm.router.swarm_dict["specific_swarm"].run(task, *args, **kwargs)
    return swarm.router.swarm_dict["default_swarm"].run(task, *args, **kwargs)

swarm = AutoSwarm(
    name="example_swarm",
    custom_router=custom_router,
    max_loops=3
)

# Running a task with custom routing
result = swarm.run(task="specific_task")
print(result)  # Output will be the result of the routed task

Example 3: Verbose Mode

swarm = AutoSwarm(
    name="example_swarm",
    verbose=True,
    max_loops=3
)

# Running a task with verbose mode enabled
result = swarm.run(task="example_task")
# Output will include detailed logs of the task execution process

Full Example 4:

First create a class with BaseSwarm -> Then wrap it in the router -> then pass that to the AutoSwarm

from swarms import BaseSwarm, AutoSwarmRouter, AutoSwarm


class FinancialReportSummarization(BaseSwarm):
    def __init__(self, name: str = None, *args, **kwargs):
        super().__init__()

    def run(self, task, *args, **kwargs):
        return task


# Add swarm to router
router = AutoSwarmRouter(swarms=[FinancialReportSummarization])

# Create AutoSwarm Instance
autoswarm = AutoSwarm(
    name="kyegomez/FinancialReportSummarization",
    description="A swarm for financial document summarizing and generation",
    verbose=True,
    router=router,
)

# Run the AutoSwarm
autoswarm.run("Analyze these documents and give me a summary:")

Summary

The AutoSwarm class provides a robust framework for managing and executing tasks using a swarm of agents. With customizable preprocessing, routing, and postprocessing functions, it is highly adaptable to various workflows and can handle complex task execution scenarios efficiently. The integration with AutoSwarmRouter enhances its flexibility, making it a powerful tool for dynamic task management.