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# `MajorityVoting` Documentation
# MajorityVoting Module Documentation
## Overview
The `MajorityVoting` module provides a mechanism for performing majority voting among a group of agents. Majority voting is a decision rule that selects the option which has the majority of votes. This is particularly useful in systems where multiple agents provide responses to a query, and the most common response needs to be identified as the final output.
The `swarms.structs` library provides a flexible architecture for creating and managing swarms of agents capable of performing tasks and making decisions based on majority voting. This documentation will guide you through the `MajorityVoting` class, explaining its purpose, architecture, and usage with examples.
### Key Concepts
## Table of Contents
- **Majority Voting**: A method to determine the most common response from a set of answers.
- **Agents**: Entities (e.g., models, algorithms) that provide responses to tasks or queries.
- **Output Parser**: A function that processes the responses from the agents before performing the majority voting.
- [Introduction](#introduction)
- [Installation](#installation)
- [The `MajorityVoting` Class](#the-majorityvoting-class)
- [Class Definition](#class-definition)
- [Parameters](#parameters)
- [Methods](#methods)
- [`__init__`](#__init__)
- [`run`](#run)
- [Usage Examples](#usage-examples)
- [Basic Usage](#basic-usage)
- [Concurrent Execution](#concurrent-execution)
- [Asynchronous Execution](#asynchronous-execution)
- [Advanced Features](#advanced-features)
- [Troubleshooting and FAQ](#troubleshooting-and-faq)
- [Conclusion](#conclusion)
- [References](#references)
## Function Definitions
## Introduction
### Function: `majority_voting`
The `swarms.structs` library introduces a mode of distributed computation through "agents" that collaborate to determine the outcome of tasks using a majority voting system. It becomes crucial in scenarios where collective decision-making is preferred over individual agent accuracy.
Performs majority voting on a list of answers and returns the most common answer.
## Installation
#### Parameters
To install the `swarms.structs` library, run the following command:
| Parameter | Type | Description |
|-----------|----------|------------------------------|
| `answers` | `List[str]` | A list of answers from different agents. |
```bash
pip install swarms-structs
```
#### Returns
| Return Value | Type | Description |
|--------------|-------|----------------------------------------|
| `answer` | `str` | The most common answer in the list. If the list is empty, returns "I don't know". |
## Class Definitions
### Class: `MajorityVoting`
## The `MajorityVoting` Class
Class representing a majority voting system for agents.
The `MajorityVoting` class is a high-level abstraction used to coordinate a group of agents that perform tasks and return results. These results are then aggregated to form a majority vote, determining the final output.
#### Parameters
### Class Definition
| Parameter | Type | Description |
|------------------|--------------|-----------------------------------------------------------------------------|
| `agents` | `List[Agent]`| A list of agents to be used in the majority voting system. |
| `output_parser` | `Callable` | A function used to parse the output of the agents. If not provided, the default `majority_voting` function is used. |
| `autosave` | `bool` | A boolean indicating whether to autosave the conversation to a file. Default is `False`. |
| `verbose` | `bool` | A boolean indicating whether to enable verbose logging. Default is `False`. |
### Parameters
### Method: `__init__`
| Parameter | Type | Default | Description |
|-----------------|------------|----------|----------------------------------------------------------------------|
| agents | List[Agent]| Required | A list of agent instances to participate in the voting process. |
| concurrent | bool | False | Enables concurrent execution using threading if set to `True`. |
| multithreaded | bool | False | Enables execution using multiple threads if set to `True`. |
| multiprocess | bool | False | Enables execution using multiple processes if set to `True`. |
| asynchronous | bool | False | Enables asynchronous execution if set to `True`. |
| output_parser | callable | None | A function to parse the output from the majority voting function. |
| autosave | bool | False | Enables automatic saving of the process state if set to `True`. (currently not used in source code) |
| verbose | bool | False | Enables verbose logging if set to `True`. |
Initializes the `MajorityVoting` system.
### Methods
#### Parameters
#### `__init__`
| Parameter | Type | Description |
|------------------|----------------|-----------------------------------------------------------------------------|
| `agents` | `List[Agent]` | A list of agents to be used in the majority voting system. |
| `output_parser` | `Callable` | A function used to parse the output of the agents. Default is the `majority_voting` function. |
| `autosave` | `bool` | A boolean indicating whether to autosave the conversation to a file. Default is `False`. |
| `verbose` | `bool` | A boolean indicating whether to enable verbose logging. Default is `False`. |
| `args` | `tuple` | Additional positional arguments. |
| `kwargs` | `dict` | Additional keyword arguments. |
The constructor for the `MajorityVoting` class. Initializes a new majority voting system with the given configuration.
### Method: `run`
*This method doesn't return any value.*
Runs the majority voting system and returns the majority vote.
#### `run`
#### Parameters
Executes the given task by all participating agents and aggregates the results through majority voting.
| Parameter | Type | Description |
|-----------|------------|------------------------------------------|
| `task` | `str` | The task to be performed by the agents. |
| `args` | `tuple` | Variable length argument list. |
| `kwargs` | `dict` | Arbitrary keyword arguments. |
| Parameter | Type | Description |
|-----------|-----------|----------------------------------|
| task | str | The task to be performed. |
| *args | list | Additional positional arguments. |
| **kwargs | dict | Additional keyword arguments. |
#### Returns
*Returns:* List[Any] - The result based on the majority vote.
| Return Value | Type | Description |
|--------------|-----------|--------------------------------------|
| `results` | `List[Any]` | The majority vote. |
## Usage Examples
### Basic Usage
### Example 1: Basic Majority Voting
```python
from swarms.structs.agent import Agent
from swarms.structs.majority_voting import MajorityVoting
def create_agent(name):
return Agent(name)
agents = [create_agent(name) for name in ["GPT-3", "Codex", "Tabnine"]]
# Initialize agents
agents = [
Agent(
agent_name="Devin",
system_prompt=(
"Autonomous agent that can interact with humans and other"
" agents. Be Helpful and Kind. Use the tools provided to"
" assist the user. Return all code in markdown format."
),
llm=llm,
max_loops="auto",
autosave=True,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
interactive=True,
tools=[terminal, browser, file_editor, create_file],
code_interpreter=True,
),
Agent(
agent_name="Codex",
system_prompt=(
"An AI coding assistant capable of writing and understanding"
" code snippets in various programming languages."
),
llm=llm,
max_loops="auto",
autosave=True,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
interactive=True,
tools=[terminal, browser, file_editor, create_file],
code_interpreter=True,
),
Agent(
agent_name="Tabnine",
system_prompt=(
"A code completion AI that provides suggestions for code"
" completion and code improvements."
),
llm=llm,
max_loops="auto",
autosave=True,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
interactive=True,
tools=[terminal, browser, file_editor, create_file],
code_interpreter=True,
),
]
# Create MajorityVoting instance
majority_voting = MajorityVoting(agents)
# Run the majority voting system
result = majority_voting.run("What is the capital of France?")
print(result) # Output: Paris
print(result) # Output: 'Paris'
```
### Concurrent Execution
### Example 2: Running a Task with Detailed Outputs
```python
majority_voting = MajorityVoting(agents, concurrent=True)
result = majority_voting.run("What is the largest continent?")
print(result) # Example Output: Asia
```
### Asynchronous Execution
from swarms.structs.agent import Agent
from swarms.structs.majority_voting import MajorityVoting
```python
majority_voting = MajorityVoting(agents, asynchronous=True)
result = majority_voting.run("What is the square root of 16?")
print(result) # Output: 4
```
# Initialize agents
agents = [
Agent(
agent_name="Devin",
system_prompt=(
"Autonomous agent that can interact with humans and other"
" agents. Be Helpful and Kind. Use the tools provided to"
" assist the user. Return all code in markdown format."
),
llm=llm,
max_loops="auto",
autosave=True,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
interactive=True,
tools=[terminal, browser, file_editor, create_file],
code_interpreter=True,
),
Agent(
agent_name="Codex",
system_prompt=(
"An AI coding assistant capable of writing and understanding"
" code snippets in various programming languages."
),
llm=llm,
max_loops="auto",
autosave=True,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
interactive=True,
tools=[terminal, browser, file_editor, create_file],
code_interpreter=True,
),
Agent(
agent_name="Tabnine",
system_prompt=(
"A code completion AI that provides suggestions for code"
" completion and code improvements."
),
llm=llm,
max_loops="auto",
autosave=True,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
interactive=True,
tools=[terminal, browser, file_editor, create_file],
code_interpreter=True,
),
]
# Create MajorityVoting instance
majority_voting = MajorityVoting(agents)
# Run the majority voting system with a different task
result = majority_voting.run("Create a new file for a plan to take over the world.")
print(result)
```
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