SpreadSheetSwarm

Overview

The SpreadSheetSwarm processes tasks concurrently across multiple agents and automatically saves execution metadata to CSV files. It supports loading agent configurations from CSV files and running tasks either from configuration or on-demand.

Installation

pip install -U swarms

Attributes

str

default:"Spreadsheet-Swarm"

The name of the swarm

str

default:"A swarm that processes tasks concurrently..."

The description of the swarm

List[Agent]

default:"None"

The agents participating in the swarm. If None, agents will be loaded from load_path

bool

default:"True"

Whether to enable autosave of swarm metadata

str

default:"None"

The file path to save the swarm metadata as a CSV file (auto-generated if None)

int

default:"1"

The number of times to repeat the swarm tasks

str

default:"None"

Path to CSV file containing agent configurations. Required if agents is None

bool

default:"False"

Enable verbose logging

Methods

run()

Run the swarm with the specified task.

def run(self, task: str = None, *args, **kwargs) -> dict

Parameters:

task (str): The task to be executed by the swarm. If None, uses tasks from config

Returns: Dictionary containing run summary with outputs and metadata

run_from_config()

Run all agents with their configured tasks concurrently.

def run_from_config(self) -> dict

Returns: Dictionary containing execution summary

load_from_csv()

Load agent configurations from a CSV file.

def load_from_csv(self)

Expected CSV format:

agent_name,description,system_prompt,task,model_name,max_loops

export_to_json()

Export the swarm outputs to JSON.

def export_to_json(self) -> str

Returns: JSON string representation of swarm outputs

Usage Examples

Basic Usage with Agents

from swarms import Agent, SpreadSheetSwarm

# Create agents
agents = [
    Agent(
        agent_name="Research-Agent",
        system_prompt="You are a research agent.",
        model_name="openai/gpt-4o",
    ),
    Agent(
        agent_name="Analysis-Agent",
        system_prompt="You are an analysis agent.",
        model_name="openai/gpt-4o",
    ),
]

# Create swarm
swarm = SpreadSheetSwarm(
    name="My-Swarm",
    agents=agents,
    max_loops=1,
    autosave=True
)

# Run with a task
result = swarm.run("Analyze the latest AI trends")

print(result)

Load from CSV Configuration

Create a CSV file (agents_config.csv):

agent_name,description,system_prompt,task,model_name,max_loops
Research-Agent,Research specialist,You are a research agent,Research quantum computing,openai/gpt-4o,1
Analysis-Agent,Data analyst,You are an analysis agent,Analyze the research findings,openai/gpt-4o,1

Then load and run:

swarm = SpreadSheetSwarm(
    name="CSV-Swarm",
    load_path="agents_config.csv",
    max_loops=1
)

# Run agents with their configured tasks
result = swarm.run_from_config()

Multiple Loops

# Run each agent multiple times
swarm = SpreadSheetSwarm(
    agents=agents,
    max_loops=3  # Each agent runs 3 times
)

result = swarm.run("Process this task multiple times")

Custom Save Path

swarm = SpreadSheetSwarm(
    name="Custom-Swarm",
    agents=agents,
    save_file_path="./results/swarm_outputs.csv",
    autosave=True
)

result = swarm.run("Custom task")

Export Results

# Run swarm
result = swarm.run("Some task")

# Export to JSON
json_output = swarm.export_to_json()
print(json_output)

# Results are automatically saved to CSV if autosave=True

Output Format

The run() method returns a dictionary:

{
    "run_id": "spreadsheet_swarm_run_abc123",
    "name": "My-Swarm",
    "description": "A swarm that processes tasks...",
    "start_time": "2024-01-01T12:00:00",
    "end_time": "2024-01-01T12:05:00",
    "tasks_completed": 6,
    "number_of_agents": 3,
    "outputs": [
        {
            "agent_name": "Research-Agent",
            "task": "Analyze the latest AI trends",
            "result": "...",
            "timestamp": "2024-01-01T12:01:00"
        },
        # ... more outputs
    ]
}

CSV Output Format

Results are automatically saved to CSV with these columns:

Run ID,Agent Name,Task,Result,Timestamp
abc-123,Research-Agent,Analyze trends,...,2024-01-01T12:00:00
abc-123,Analysis-Agent,Analyze trends,...,2024-01-01T12:00:05

Features

Concurrent Execution: All agents run tasks in parallel for maximum performance
Automatic CSV Logging: All executions are logged to CSV files automatically
CSV Configuration: Load agent configurations from CSV files
Multiple Loops: Run each agent multiple times with max_loops
Workspace Integration: Automatically uses workspace directory from environment
JSON Export: Export results to JSON format
Metadata Tracking: Tracks timestamps, run IDs, and execution metadata

Core Classes

Multi-Agent Harnesses

Tools & Utilities

Deployment

SpreadSheetSwarm

Overview

Installation

Attributes

Methods

run()

run_from_config()

load_from_csv()

export_to_json()

Usage Examples

Basic Usage with Agents

Load from CSV Configuration

Multiple Loops

Custom Save Path

Export Results

Output Format

CSV Output Format

Features

​Overview

​Installation

​Attributes

​Methods

​run()

​run_from_config()

​load_from_csv()

​export_to_json()

​Usage Examples

​Basic Usage with Agents

​Load from CSV Configuration

​Multiple Loops

​Custom Save Path

​Export Results

​Output Format

​CSV Output Format

​Features

Overview

Installation

Attributes

Methods

run()

run_from_config()

load_from_csv()

export_to_json()

Usage Examples

Basic Usage with Agents

Load from CSV Configuration

Multiple Loops

Custom Save Path

Export Results

Output Format

CSV Output Format

Features