Extending JuliaOS

This comprehensive guide covers how to extend JuliaOS with new functionality, including creating custom agents, implementing new swarm algorithms, adding blockchain networks, integrating new DEXes, implementing bridge protocols, and extending wallet support.

Overview

JuliaOS is designed to be highly extensible, allowing developers to add new components and enhance existing functionality. The modular architecture makes it straightforward to extend various parts of the system without affecting other components.

This guide covers the following extension points:

1. Custom Agents: Create specialized agent types with custom behavior

2. Swarm Algorithms: Implement new optimization or coordination algorithms

3. Blockchain Networks: Add support for additional blockchain networks

4. DEX Integration: Connect to new decentralized exchanges

5. Bridge Protocols: Implement new cross-chain bridge protocols

6. Wallet Support: Add support for new wallet types

Each section provides step-by-step instructions, code examples, and best practices for extending JuliaOS.

Extending Agents & Swarms

Custom Agent Creation

JuliaOS allows you to create specialized agent types with custom behaviors beyond the built-in types (e.g., Trading, Arbitrage, Research). This section provides a detailed guide on creating custom agent types.

Step 1: Define Agent Logic (Julia)

Location: Create a new module in /julia/src/agents/ directory (e.g., /julia/src/agents/CustomAgents.jl).

1. Define Agent State: Create a Julia struct to hold the agent's state if needed

2. Implement Core Functions: Create functions for agent creation, initialization, execution, and other lifecycle events

3. Define Agent Behavior: Implement the specific logic for your agent type

# Example: /julia/src/agents/DataAnalysisAgent.jl
module DataAnalysisAgents

using ..AgentSystem
using ..Storage
using JSON

# Define agent state structure
struct DataAnalysisAgentState
    data_sources::Vector{String}
    analysis_methods::Vector{String}
    refresh_interval::Int  # in seconds
    last_analysis_time::Float64
    results_cache::Dict{String, Any}
 end

"""
    create_data_analysis_agent(config::Dict) -> Dict

Create a new data analysis agent with the specified configuration.

# Arguments
- `config::Dict`: Configuration parameters including data_sources, analysis_methods, and refresh_interval

# Returns
- `Dict`: The created agent object with an assigned ID
"""
function create_data_analysis_agent(config::Dict)
    # Validate required configuration parameters
    if !haskey(config, "data_sources") || !haskey(config, "analysis_methods")
        throw(ArgumentError("Data analysis agent requires data_sources and analysis_methods"))
    end

    # Set default values for optional parameters
    refresh_interval = get(config, "refresh_interval", 3600)  # Default: 1 hour

    # Create agent state
    state = DataAnalysisAgentState(
        config["data_sources"],
        config["analysis_methods"],
        refresh_interval,
        time(),  # Current time
        Dict()   # Empty results cache
    )

    # Create the agent using AgentSystem's create_agent function
    agent = AgentSystem.create_agent(
        get(config, "name", "DataAnalysisAgent"),
        "data_analysis",
        config,
        state
    )

    return agent
end

"""
    initialize_agent(agent::Dict) -> Bool

Initialize the data analysis agent, setting up any necessary resources.

# Arguments
- `agent::Dict`: The agent object

# Returns
- `Bool`: True if initialization was successful
"""
function initialize_agent(agent::Dict)
    # Perform any necessary initialization
    # For example, connect to data sources, load models, etc.

    # Log initialization
    AgentSystem.log_agent_event(agent["id"], "Initialized data analysis agent")

    return true
end

"""
    run_agent_loop!(agent::Dict) -> Nothing

Main execution loop for the data analysis agent.

# Arguments
- `agent::Dict`: The agent object
"""
function run_agent_loop!(agent::Dict)
    state = agent["state"]

    while AgentSystem.is_agent_running(agent["id"])
        try
            # Check if it's time to refresh analysis
            current_time = time()
            if current_time - state.last_analysis_time >= state.refresh_interval
                # Perform data analysis
                results = perform_analysis(agent)

                # Update cache and last analysis time
                state.results_cache = results
                state.last_analysis_time = current_time

                # Store results in persistent storage
                Storage.store_agent_data(agent["id"], "analysis_results", JSON.json(results))

                # Log successful analysis
                AgentSystem.log_agent_event(agent["id"], "Completed data analysis cycle")
            end

            # Sleep to avoid busy waiting
            sleep(min(10, state.refresh_interval))  # Sleep for 10 seconds or refresh interval, whichever is smaller
        catch e
            # Log error and continue
            AgentSystem.log_agent_error(agent["id"], "Error in agent loop: $e")
            sleep(30)  # Sleep longer after an error
        end
    end
end

"""
    perform_analysis(agent::Dict) -> Dict

Perform data analysis based on the agent's configuration.

# Arguments
- `agent::Dict`: The agent object

# Returns
- `Dict`: Analysis results
"""
function perform_analysis(agent::Dict)
    state = agent["state"]
    results = Dict()

    # Process each data source
    for source in state.data_sources
        # Fetch data from source
        data = fetch_data(source)

        # Apply each analysis method
        for method in state.analysis_methods
            result = apply_analysis_method(method, data)
            results["$(source)_$(method)"] = result
        end
    end

    return results
end

# Helper functions for data fetching and analysis
function fetch_data(source::String)
    # Implementation depends on the data source
    # Could be API calls, database queries, etc.
    # ...
    return Dict("sample_data" => [1, 2, 3, 4, 5])  # Placeholder
end

function apply_analysis_method(method::String, data::Dict)
    # Implementation depends on the analysis method
    # Could be statistical analysis, ML models, etc.
    # ...
    return Dict("result" => "analysis output")  # Placeholder
end

"""
    execute_task(agent::Dict, task::Dict) -> Dict

Execute a specific task with the data analysis agent.

# Arguments
- `agent::Dict`: The agent object
- `task::Dict`: Task parameters

# Returns
- `Dict`: Task results
"""
function execute_task(agent::Dict, task::Dict)
    state = agent["state"]

    if !haskey(task, "action")
        return Dict("error" => "Task must specify an action")
    end

    action = task["action"]

    if action == "get_latest_results"
        # Return the latest analysis results
        return Dict("results" => state.results_cache)
    elseif action == "run_analysis_now"
        # Force an immediate analysis
        results = perform_analysis(agent)
        state.results_cache = results
        state.last_analysis_time = time()
        return Dict("results" => results)
    elseif action == "add_data_source"
        # Add a new data source
        if !haskey(task, "source")
            return Dict("error" => "Missing source parameter")
        end
        push!(state.data_sources, task["source"])
        return Dict("success" => true, "data_sources" => state.data_sources)
    elseif action == "add_analysis_method"
        # Add a new analysis method
        if !haskey(task, "method")
            return Dict("error" => "Missing method parameter")
        end
        push!(state.analysis_methods, task["method"])
        return Dict("success" => true, "analysis_methods" => state.analysis_methods)
    else
        return Dict("error" => "Unknown action: $action")
    end
end

"""
    cleanup_agent(agent::Dict) -> Bool

Clean up resources when the agent is stopped or deleted.

# Arguments
- `agent::Dict`: The agent object

# Returns
- `Bool`: True if cleanup was successful
"""
function cleanup_agent(agent::Dict)
    # Perform any necessary cleanup
    # For example, close connections, release resources, etc.

    # Log cleanup
    AgentSystem.log_agent_event(agent["id"], "Cleaned up data analysis agent")

    return true
end

# Export the module's functions
export create_data_analysis_agent, initialize_agent, run_agent_loop!, execute_task, cleanup_agent

end # module

Step 2: Register Agent Type (Julia)

Location: /julia/src/Agents.jl or where the AGENT_TYPES dictionary is defined.

1. Import Your Module: Add an import statement for your custom agent module

2. Register Agent Type: Add your agent type string and its creation function to the AGENT_TYPES dictionary

# In /julia/src/Agents.jl or similar

# Import your custom agent module
include("agents/DataAnalysisAgent.jl")
using .DataAnalysisAgents

# Register the agent type
global AGENT_TYPES["data_analysis"] = DataAnalysisAgents.create_data_analysis_agent

# Register lifecycle handlers if needed
global AGENT_INITIALIZERS["data_analysis"] = DataAnalysisAgents.initialize_agent
global AGENT_RUNNERS["data_analysis"] = DataAnalysisAgents.run_agent_loop!
global AGENT_TASK_HANDLERS["data_analysis"] = DataAnalysisAgents.execute_task
global AGENT_CLEANERS["data_analysis"] = DataAnalysisAgents.cleanup_agent

Step 3: Add Command Handlers (Julia - Optional)

Location: /julia/src/commandhandlers.jl or where command handlers are defined.

If your agent needs specific commands beyond the standard ones (create, start, stop, status), add handlers for them:

# In /julia/src/commandhandlers.jl or similar

# Add a command handler for data analysis specific operations
function handle_data_analysis_command(command::String, params::Dict)
    if command == "agents.data_analysis.add_source"
        # Validate parameters
        if !haskey(params, "agent_id") || !haskey(params, "source")
            return error_response("Missing required parameters: agent_id and source")
        end

        # Get the agent
        agent = AgentSystem.get_agent(params["agent_id"])
        if agent === nothing
            return error_response("Agent not found")
        end

        # Execute the task
        result = DataAnalysisAgents.execute_task(agent, Dict(
            "action" => "add_data_source",
            "source" => params["source"]
        ))

        return success_response(result)
    elseif command == "agents.data_analysis.get_results"
        # Similar implementation for getting results
        # ...
    end

    # If command not recognized, return error
    return error_response("Unknown command: $command")
end

# Register the command handler in the main command dispatcher
COMMAND_HANDLERS["agents.data_analysis"] = handle_data_analysis_command

Step 4: Update Frontend Interfaces

CLI Integration

Location: /packages/cli/src/menus/agents.js or similar.

// Add your agent type to the agent creation menu
const agentTypes = [
  { name: 'Trading Agent', value: 'trading' },
  { name: 'Arbitrage Agent', value: 'arbitrage' },
  // Add your new agent type
  { name: 'Data Analysis Agent', value: 'data_analysis' },
];

// Add configuration prompts for your agent type
const getAgentConfigPrompts = (type) => {
  switch (type) {
    // Existing cases...

    case 'data_analysis':
      return [
        {
          type: 'input',
          name: 'data_sources',
          message: 'Enter data sources (comma-separated):',
          filter: (input) => input.split(',').map(s => s.trim()),
        },
        {
          type: 'input',
          name: 'analysis_methods',
          message: 'Enter analysis methods (comma-separated):',
          filter: (input) => input.split(',').map(s => s.trim()),
        },
        {
          type: 'number',
          name: 'refresh_interval',
          message: 'Enter refresh interval (seconds):',
          default: 3600,
        },
      ];

    // Default case...
  }
};

// Add agent-specific commands to the agent menu
const getAgentCommands = (agent) => {
  const commonCommands = [/* common commands */];

  // Add type-specific commands
  if (agent.type === 'data_analysis') {
    return [
      ...commonCommands,
      {
        name: 'Run Analysis Now',
        value: 'run_analysis_now',
      },
      {
        name: 'View Latest Results',
        value: 'view_results',
      },
      {
        name: 'Add Data Source',
        value: 'add_data_source',
      },
      {
        name: 'Add Analysis Method',
        value: 'add_analysis_method',
      },
    ];
  }

  return commonCommands;
};

// Implement handlers for the agent-specific commands
const handleAgentCommand = async (agent, command) => {
  // Existing command handlers...

  if (agent.type === 'data_analysis') {
    if (command === 'run_analysis_now') {
      const result = await bridge.execute('agents.execute_task', {
        agent_id: agent.id,
        task: { action: 'run_analysis_now' },
      });

      console.log('Analysis results:', JSON.stringify(result.data.results, null, 2));
      return;
    }

    if (command === 'view_results') {
      const result = await bridge.execute('agents.execute_task', {
        agent_id: agent.id,
        task: { action: 'get_latest_results' },
      });

      console.log('Latest results:', JSON.stringify(result.data.results, null, 2));
      return;
    }

    // Implement other command handlers...
  }

  // Default handler...
};

TypeScript/JavaScript Framework Integration

Location: /packages/framework/src/agents.ts or similar.

// Add type definitions for your agent type
export interface DataAnalysisAgentConfig {
  data_sources: string[];
  analysis_methods: string[];
  refresh_interval?: number;
}

// Add a specialized class for your agent type
export class DataAnalysisAgent extends Agent {
  constructor(bridge: JuliaBridge, id: string, data: AgentData) {
    super(bridge, id, data);
  }

  // Add specialized methods
  async runAnalysisNow(): Promise<any> {
    const result = await this.executeTask({
      action: 'run_analysis_now',
    });

    return result;
  }

  async getLatestResults(): Promise<any> {
    const result = await this.executeTask({
      action: 'get_latest_results',
    });

    return result.results;
  }

  async addDataSource(source: string): Promise<string[]> {
    const result = await this.executeTask({
      action: 'add_data_source',
      source,
    });

    return result.data_sources;
  }

  async addAnalysisMethod(method: string): Promise<string[]> {
    const result = await this.executeTask({
      action: 'add_analysis_method',
      method,
    });

    return result.analysis_methods;
  }

  // Factory method for creating data analysis agents
  static async create(
    agents: Agents,
    name: string,
    config: DataAnalysisAgentConfig
  ): Promise<DataAnalysisAgent> {
    const agent = await agents.createAgent({
      name,
      type: 'data_analysis',
      config,
    });

    return new DataAnalysisAgent(agents.bridge, agent.id, agent);
  }
}

Python Wrapper Integration

Location: /packages/python-wrapper/juliaos/agents/specialized.py or similar.

from typing import List, Dict, Any, Optional
from ..client import JuliaOS
from .base import Agent

class DataAnalysisAgent(Agent):
    """A specialized agent for data analysis tasks."""

    def __init__(self, client: JuliaOS, agent_id: str, data: Dict[str, Any]):
        super().__init__(client, agent_id, data)

    async def run_analysis_now(self) -> Dict[str, Any]:
        """Run the analysis immediately and return results."""
        result = await self.execute_task({
            "action": "run_analysis_now"
        })

        return result["results"]

    async def get_latest_results(self) -> Dict[str, Any]:
        """Get the latest analysis results."""
        result = await self.execute_task({
            "action": "get_latest_results"
        })

        return result["results"]

    async def add_data_source(self, source: str) -> List[str]:
        """Add a new data source to the agent.

        Args:
            source: The data source to add

        Returns:
            Updated list of data sources
        """
        result = await self.execute_task({
            "action": "add_data_source",
            "source": source
        })

        return result["data_sources"]

    async def add_analysis_method(self, method: str) -> List[str]:
        """Add a new analysis method to the agent.

        Args:
            method: The analysis method to add

        Returns:
            Updated list of analysis methods
        """
        result = await self.execute_task({
            "action": "add_analysis_method",
            "method": method
        })

        return result["analysis_methods"]

    @classmethod
    async def create(
        cls,
        client: JuliaOS,
        name: str,
        data_sources: List[str],
        analysis_methods: List[str],
        refresh_interval: Optional[int] = 3600
    ) -> "DataAnalysisAgent":
        """Create a new data analysis agent.

        Args:
            client: JuliaOS client instance
            name: Name of the agent
            data_sources: List of data sources to analyze
            analysis_methods: List of analysis methods to apply
            refresh_interval: Interval in seconds between analyses (default: 3600)

        Returns:
            The created DataAnalysisAgent instance
        """
        agent = await client.agents.create_agent(
            name=name,
            agent_type="data_analysis",
            config={
                "parameters": {
                    "data_sources": data_sources,
                    "analysis_methods": analysis_methods,
                    "refresh_interval": refresh_interval
                }
            }
        )

        return cls(client, agent.id, agent._data)

Step 5: Testing Your Custom Agent

1. Unit Tests: Create unit tests for your agent's functionality

# In /julia/test/test_data_analysis_agent.jl

using Test
using JuliaOS.Agents
using JuliaOS.AgentSystem

@testset "DataAnalysisAgent" begin
    # Test agent creation
    config = Dict(
        "name" => "TestDataAnalysisAgent",
        "data_sources" => ["source1", "source2"],
        "analysis_methods" => ["method1", "method2"],
        "refresh_interval" => 60
    )

    agent = Agents.create_agent("TestDataAnalysisAgent", "data_analysis", config)

    @test agent !== nothing
    @test agent["type"] == "data_analysis"
    @test agent["state"].data_sources == ["source1", "source2"]
    @test agent["state"].analysis_methods == ["method1", "method2"]
    @test agent["state"].refresh_interval == 60

    # Test task execution
    result = Agents.execute_task(agent["id"], Dict("action" => "add_data_source", "source" => "source3"))
    @test result["success"] == true
    @test "source3" in result["data_sources"]

    # Test other functionality
    # ...
end

1. Integration Tests: Test the agent through the bridge interface

// In /packages/framework/tests/agents.test.ts

describe('DataAnalysisAgent', () => {
  let bridge: JuliaBridge;
  let agents: Agents;
  let agent: DataAnalysisAgent;

  beforeAll(async () => {
    bridge = new JuliaBridge({ host: 'localhost', port: 8052 });
    await bridge.initialize();
    agents = new Agents(bridge);
  });

  afterAll(async () => {
    await bridge.disconnect();
  });

  it('should create a data analysis agent', async () => {
    agent = await DataAnalysisAgent.create(
      agents,
      'TestDataAnalysisAgent',
      {
        data_sources: ['source1', 'source2'],
        analysis_methods: ['method1', 'method2'],
        refresh_interval: 60,
      }
    );

    expect(agent).toBeDefined();
    expect(agent.id).toBeDefined();
    expect(agent.type).toBe('data_analysis');
  });

  it('should add a data source', async () => {
    const sources = await agent.addDataSource('source3');
    expect(sources).toContain('source3');
  });

  // Additional tests
  // ...
});

Best Practices for Custom Agents

1. Modular Design: Keep your agent's functionality modular and focused on a specific purpose

2. Error Handling: Implement comprehensive error handling in all agent functions

3. Documentation: Document your agent's purpose, configuration parameters, and behavior

4. Testing: Write thorough tests for all agent functionality

5. Resource Management: Properly initialize and clean up resources used by your agent

6. Performance: Consider the performance implications of your agent's behavior, especially for long-running operations

7. Security: Validate all inputs and consider security implications of your agent's actions

8. Compatibility: Ensure your agent works with the existing JuliaOS architecture and interfaces

Implementing New Swarm Algorithms

JuliaOS supports various swarm intelligence algorithms for optimization and coordination tasks. This section provides a detailed guide on implementing new swarm algorithms.

Step 1: Define Algorithm Logic (Julia)

Location: Create a new module in /julia/src/algorithms/ directory (e.g., /julia/src/algorithms/FireflyAlgorithm.jl).

1. Define Algorithm State: Create a Julia struct to hold the algorithm's state

2. Implement Core Functions: Create functions for initialization, iteration, and convergence checking

3. Define Algorithm Behavior: Implement the specific logic for your swarm algorithm

# Example: /julia/src/algorithms/FireflyAlgorithm.jl
module FireflyAlgorithm

export initialize, iterate, is_converged, get_result

using Random
using LinearAlgebra

# Define algorithm state structure
mutable struct FireflyState
    population::Vector{Vector{Float64}}  # Positions of fireflies
    intensities::Vector{Float64}         # Light intensities (fitness values)
    best_position::Vector{Float64}       # Best position found
    best_value::Float64                  # Best fitness value
    alpha::Float64                       # Randomization parameter
    beta0::Float64                       # Attractiveness at distance 0
    gamma::Float64                       # Light absorption coefficient
    iteration::Int                       # Current iteration

    # Constructor with default values
    function FireflyState(dimensions::Int, population_size::Int, bounds::Vector{Tuple{Float64, Float64}})
        # Initialize population randomly within bounds
        population = []
        for i in 1:population_size
            position = []
            for d in 1:dimensions
                bound = bounds[min(d, length(bounds))]
                lower, upper = bound[1], bound[2]
                push!(position, lower + rand() * (upper - lower))
            end
            push!(population, position)
        end

        new(
            population,
            zeros(population_size),  # Intensities will be calculated during initialization
            zeros(dimensions),       # Best position will be updated during initialization
            Inf,                     # Best value (minimization problem)
            0.2,                     # Default alpha
            1.0,                     # Default beta0
            1.0,                     # Default gamma
            0                        # Initial iteration
        )
    end
end

"""
    initialize(config::Dict, objective_function::Function) -> FireflyState

Initialize the Firefly Algorithm with the given configuration and objective function.

# Arguments
- `config::Dict`: Configuration parameters including dimensions, bounds, population_size, etc.
- `objective_function::Function`: The function to optimize

# Returns
- `FireflyState`: The initialized algorithm state
"""
function initialize(config::Dict, objective_function::Function)
    # Extract parameters
    dimensions = config["dimensions"]
    bounds = config["bounds"]
    population_size = get(config, "population_size", 25)
    minimize = get(config, "minimize", true)  # Default to minimization

    # Create state
    state = FireflyState(dimensions, population_size, bounds)

    # Set algorithm parameters
    state.alpha = get(config, "alpha", 0.2)
    state.beta0 = get(config, "beta0", 1.0)
    state.gamma = get(config, "gamma", 1.0)

    # Calculate initial intensities (fitness values)
    for i in 1:length(state.population)
        fitness = objective_function(state.population[i])
        state.intensities[i] = minimize ? fitness : -fitness  # Convert to minimization problem if needed

        # Update best position if better
        if state.intensities[i] < state.best_value
            state.best_value = state.intensities[i]
            state.best_position = copy(state.population[i])
        end
    end

    return state
end

"""
    iterate(state::FireflyState, config::Dict, objective_function::Function) -> FireflyState

Perform one iteration of the Firefly Algorithm.

# Arguments
- `state::FireflyState`: The current algorithm state
- `config::Dict`: Configuration parameters
- `objective_function::Function`: The function to optimize

# Returns
- `FireflyState`: The updated algorithm state
"""
function iterate(state::FireflyState, config::Dict, objective_function::Function)
    bounds = config["bounds"]
    dimensions = config["dimensions"]
    minimize = get(config, "minimize", true)  # Default to minimization

    # Increment iteration counter
    state.iteration += 1

    # Move each firefly
    new_population = copy(state.population)

    for i in 1:length(state.population)
        for j in 1:length(state.population)
            # Skip if i == j or if j is not brighter than i
            if i == j || state.intensities[j] >= state.intensities[i]
                continue
            end

            # Calculate distance between fireflies
            r = norm(state.population[i] - state.population[j])

            # Calculate attractiveness
            beta = state.beta0 * exp(-state.gamma * r^2)

            # Move firefly i towards j
            for d in 1:dimensions
                # Movement formula: x_i = x_i + β * (x_j - x_i) + α * (rand - 0.5)
                new_population[i][d] += beta * (state.population[j][d] - state.population[i][d]) +
                                       state.alpha * (rand() - 0.5)

                # Apply bounds
                bound = bounds[min(d, length(bounds))]
                lower, upper = bound[1], bound[2]
                new_population[i][d] = clamp(new_population[i][d], lower, upper)
            end
        end
    end

    # Update population
    state.population = new_population

    # Recalculate intensities and update best position
    for i in 1:length(state.population)
        fitness = objective_function(state.population[i])
        state.intensities[i] = minimize ? fitness : -fitness  # Convert to minimization problem if needed

        # Update best position if better
        if state.intensities[i] < state.best_value
            state.best_value = state.intensities[i]
            state.best_position = copy(state.population[i])
        end
    end

    return state
end

"""
    is_converged(state::FireflyState, config::Dict) -> Bool

Check if the Firefly Algorithm has converged.

# Arguments
- `state::FireflyState`: The current algorithm state
- `config::Dict`: Configuration parameters

# Returns
- `Bool`: True if the algorithm has converged
"""
function is_converged(state::FireflyState, config::Dict)
    max_iterations = get(config, "max_iterations", 1000)
    tolerance = get(config, "tolerance", 1e-6)

    # Check if maximum iterations reached
    if state.iteration >= max_iterations
        return true
    end

    # Check if population has converged (all fireflies are close to each other)
    max_distance = 0.0
    for i in 1:length(state.population)
        for j in (i+1):length(state.population)
            distance = norm(state.population[i] - state.population[j])
            max_distance = max(max_distance, distance)
        end
    end

    return max_distance < tolerance
end

"""
    get_result(state::FireflyState, config::Dict) -> Dict

Get the result of the Firefly Algorithm optimization.

# Arguments
- `state::FireflyState`: The current algorithm state
- `config::Dict`: Configuration parameters

# Returns
- `Dict`: The optimization result
"""
function get_result(state::FireflyState, config::Dict)
    minimize = get(config, "minimize", true)  # Default to minimization

    # Convert back to original problem (maximization or minimization)
    best_fitness = minimize ? state.best_value : -state.best_value

    return Dict(
        "best_position" => state.best_position,
        "best_fitness" => best_fitness,
        "iterations" => state.iteration,
        "converged" => is_converged(state, config)
    )
end

end # module

Step 2: Register Algorithm (Julia)

Location: /julia/src/SwarmManager/AlgorithmFactory.jl or where the algorithm factory is defined.

1. Import Your Module: Add an import statement for your custom algorithm module

2. Register Algorithm: Update the algorithm factory to recognize your algorithm

# In /julia/src/SwarmManager/AlgorithmFactory.jl

# Import your custom algorithm module
include("../algorithms/FireflyAlgorithm.jl")
using .FireflyAlgorithm

# Update the create_algorithm function
function create_algorithm(algorithm_type::String, config::Dict)
    if algorithm_type == "pso"
        return PSO.initialize(config)
    elseif algorithm_type == "de"
        return DE.initialize(config)
    # Add your new algorithm
    elseif algorithm_type == "firefly"
        return FireflyAlgorithm.initialize(config)
    else
        throw(ArgumentError("Unknown algorithm type: $algorithm_type"))
    end
end

# Update other factory functions as needed
function iterate_algorithm(algorithm_type::String, state::Any, config::Dict, objective_function::Function)
    if algorithm_type == "pso"
        return PSO.iterate(state, config, objective_function)
    elseif algorithm_type == "de"
        return DE.iterate(state, config, objective_function)
    # Add your new algorithm
    elseif algorithm_type == "firefly"
        return FireflyAlgorithm.iterate(state, config, objective_function)
    else
        throw(ArgumentError("Unknown algorithm type: $algorithm_type"))
    end
end

# Similar updates for is_converged and get_result functions

Step 3: Update Frontend Interfaces

CLI Integration

Location: /packages/cli/src/menus/swarms.js or similar.

// Add your algorithm to the swarm creation menu
const swarmAlgorithms = [
  { name: 'Particle Swarm Optimization (PSO)', value: 'pso' },
  { name: 'Differential Evolution (DE)', value: 'de' },
  // Add your new algorithm
  { name: 'Firefly Algorithm (FA)', value: 'firefly' },
];

// Add configuration prompts for your algorithm
const getSwarmConfigPrompts = (algorithm) => {
  const commonPrompts = [
    // Common prompts for all algorithms
  ];

  switch (algorithm) {
    // Existing cases...

    case 'firefly':
      return [
        ...commonPrompts,
        {
          type: 'number',
          name: 'population_size',
          message: 'Enter population size:',
          default: 25,
        },
        {
          type: 'number',
          name: 'alpha',
          message: 'Enter randomization parameter (alpha):',
          default: 0.2,
        },
        {
          type: 'number',
          name: 'beta0',
          message: 'Enter attractiveness at distance 0 (beta0):',
          default: 1.0,
        },
        {
          type: 'number',
          name: 'gamma',
          message: 'Enter light absorption coefficient (gamma):',
          default: 1.0,
        },
      ];

    // Default case...
  }
};

TypeScript/JavaScript Framework Integration

Location: /packages/framework/src/swarms.ts or similar.

// Add type definitions for your algorithm
export interface FireflyAlgorithmConfig {
  population_size?: number;
  alpha?: number;
  beta0?: number;
  gamma?: number;
  dimensions: number;
  bounds: [number, number][];
  minimize?: boolean;
  max_iterations?: number;
  tolerance?: number;
}

// Add a specialized class for your algorithm
export class FireflySwarm extends Swarm {
  constructor(bridge: JuliaBridge, id: string, data: SwarmData) {
    super(bridge, id, data);
  }

  // Factory method for creating firefly swarms
  static async create(
    swarms: Swarms,
    name: string,
    config: FireflyAlgorithmConfig
  ): Promise<FireflySwarm> {
    const swarm = await swarms.createSwarm({
      name,
      algorithm: 'firefly',
      config,
    });

    return new FireflySwarm(swarms.bridge, swarm.id, swarm);
  }
}

Python Wrapper Integration

Location: /packages/python-wrapper/juliaos/swarms/algorithms.py or similar.

from typing import List, Dict, Any, Optional, Tuple, Union
from ..client import JuliaOS
from .base import Swarm

class FireflySwarm(Swarm):
    """A swarm using the Firefly Algorithm for optimization."""

    def __init__(self, client: JuliaOS, swarm_id: str, data: Dict[str, Any]):
        super().__init__(client, swarm_id, data)

    @classmethod
    async def create(
        cls,
        client: JuliaOS,
        name: str,
        dimensions: int,
        bounds: List[Tuple[float, float]],
        population_size: int = 25,
        alpha: float = 0.2,
        beta0: float = 1.0,
        gamma: float = 1.0,
        minimize: bool = True,
        max_iterations: int = 1000,
        tolerance: float = 1e-6
    ) -> "FireflySwarm":
        """Create a new swarm using the Firefly Algorithm.

        Args:
            client: JuliaOS client instance
            name: Name of the swarm
            dimensions: Number of dimensions in the search space
            bounds: List of (min, max) tuples for each dimension
            population_size: Number of fireflies in the swarm
            alpha: Randomization parameter
            beta0: Attractiveness at distance 0
            gamma: Light absorption coefficient
            minimize: Whether to minimize (True) or maximize (False) the objective function
            max_iterations: Maximum number of iterations
            tolerance: Convergence tolerance

        Returns:
            The created FireflySwarm instance
        """
        swarm = await client.swarms.create_swarm(
            name=name,
            swarm_type="optimization",
            algorithm="firefly",
            dimensions=dimensions,
            bounds=bounds,
            config={
                "population_size": population_size,
                "alpha": alpha,
                "beta0": beta0,
                "gamma": gamma,
                "minimize": minimize,
                "max_iterations": max_iterations,
                "tolerance": tolerance
            }
        )

        return cls(client, swarm.id, swarm._data)

Step 4: Testing Your Algorithm

1. Unit Tests: Create unit tests for your algorithm's functionality

# In /julia/test/test_firefly_algorithm.jl

using Test
using JuliaOS.SwarmManager
using JuliaOS.SwarmManager.AlgorithmFactory
using ..FireflyAlgorithm

@testset "FireflyAlgorithm" begin
    # Test function to optimize (sphere function)
    sphere(x) = sum(x.^2)

    # Test algorithm initialization
    config = Dict(
        "dimensions" => 2,
        "bounds" => [(-10.0, 10.0), (-10.0, 10.0)],
        "population_size" => 10,
        "max_iterations" => 50,
        "tolerance" => 1e-4
    )

    # Initialize algorithm
    state = FireflyAlgorithm.initialize(config, sphere)

    @test state !== nothing
    @test length(state.population) == 10
    @test state.iteration == 0

    # Run a few iterations
    for i in 1:20
        state = FireflyAlgorithm.iterate(state, config, sphere)
    end

    # Check that optimization made progress
    @test state.best_value < 10.0  # Should be much better than random initialization
    @test length(state.best_position) == 2
    @test state.iteration == 20

    # Test convergence
    # Run until convergence or max iterations
    while !FireflyAlgorithm.is_converged(state, config) && state.iteration < config["max_iterations"]
        state = FireflyAlgorithm.iterate(state, config, sphere)
    end

    result = FireflyAlgorithm.get_result(state, config)
    @test result["converged"] == true
    @test result["best_fitness"] < 0.1  # Should be close to optimal (0.0)

    # Test through the algorithm factory
    factory_state = AlgorithmFactory.create_algorithm("firefly", config)
    @test factory_state !== nothing

    # Test factory iteration
    factory_state = AlgorithmFactory.iterate_algorithm("firefly", factory_state, config, sphere)
    @test factory_state !== nothing
    @test factory_state.iteration == 1
end

1. Integration Tests: Test the algorithm through the bridge interface

// In /packages/framework/tests/swarms.test.ts

describe('FireflySwarm', () => {
  let bridge: JuliaBridge;
  let swarms: Swarms;
  let swarm: FireflySwarm;

  beforeAll(async () => {
    bridge = new JuliaBridge({ host: 'localhost', port: 8052 });
    await bridge.initialize();
    swarms = new Swarms(bridge);
  });

  afterAll(async () => {
    await bridge.disconnect();
  });

  it('should create a firefly swarm', async () => {
    swarm = await FireflySwarm.create(
      swarms,
      'TestFireflySwarm',
      {
        dimensions: 2,
        bounds: [[-10, 10], [-10, 10]],
        population_size: 10,
        max_iterations: 50,
      }
    );

    expect(swarm).toBeDefined();
    expect(swarm.id).toBeDefined();
    expect(swarm.algorithm).toBe('firefly');
  });

  it('should optimize a function', async () => {
    // Define a simple sphere function
    const functionId = 'sphere';
    await swarms.setObjectiveFunction({
      functionId,
      functionCode: 'function(x) return sum(x.^2) end',
      functionType: 'julia',
    });

    // Run optimization
    const result = await swarm.runOptimization({
      functionId,
      maxIterations: 50,
      tolerance: 1e-4,
    });

    expect(result).toBeDefined();
    expect(result.bestFitness).toBeLessThan(0.1);  // Should be close to optimal (0.0)
    expect(result.bestPosition).toHaveLength(2);
    expect(result.iterations).toBeGreaterThan(0);
    expect(result.converged).toBe(true);
  });
});

Best Practices for Swarm Algorithms

1. Algorithm Selection: Choose algorithms appropriate for the problem domain

2. Parameter Tuning: Provide sensible defaults but allow customization of algorithm parameters

3. Convergence Criteria: Implement robust convergence checks to avoid premature convergence or excessive iterations

4. Boundary Handling: Properly handle boundary constraints to keep solutions within the feasible region

5. Performance Optimization: Optimize computationally intensive parts of the algorithm

6. Numerical Stability: Handle potential numerical issues (division by zero, overflow, etc.)

7. Logging: Provide informative logging to track algorithm progress

8. Documentation: Document the algorithm's principles, parameters, and behavior

9. Testing: Test the algorithm on standard benchmark functions

10. Visualization: Consider adding visualization capabilities for algorithm behavior

Adding Bridges & Wallets

Adding a New Bridge

JuliaOS supports various cross-chain bridge protocols for transferring assets between different blockchain networks. This section provides a detailed guide on implementing new bridge protocols.

Step 1: Implement Bridge Logic (Node.js/TypeScript)

Location: Create a new directory in /packages/bridges/ (e.g., /packages/bridges/axelar).

1. Define Bridge Interface: Create a class that implements the common bridge interface

2. Implement Protocol-Specific Logic: Add methods for interacting with the bridge protocol

3. Handle Error Cases: Implement comprehensive error handling

// Example: /packages/bridges/axelar/src/index.ts
import { AxelarQueryAPI, AxelarGMPRecoveryAPI, Environment } from '@axelar-network/axelarjs-sdk';
import { ethers } from 'ethers';
import { BridgeProvider, TransferParams, TransferStatus, BridgeConfig } from '@juliaos/bridge-core';

export interface AxelarBridgeConfig extends BridgeConfig {
  environment: 'mainnet' | 'testnet';
  apiKey?: string;
}

/**
 * Axelar Bridge Provider implementation
 */
export class AxelarBridge implements BridgeProvider {
  private axelarQuery: AxelarQueryAPI;
  private axelarGMPRecovery: AxelarGMPRecoveryAPI;
  private config: AxelarBridgeConfig;

  /**
   * Create a new Axelar bridge provider
   * @param config Bridge configuration
   */
  constructor(config: AxelarBridgeConfig) {
    this.config = {
      ...config,
      environment: config.environment || 'mainnet',
    };

    const environment = this.config.environment === 'mainnet' ? Environment.MAINNET : Environment.TESTNET;
    this.axelarQuery = new AxelarQueryAPI({ environment });
    this.axelarGMPRecovery = new AxelarGMPRecoveryAPI({ environment });
  }

  /**
   * Get supported source chains
   * @returns Array of supported source chain identifiers
   */
  async getSupportedSourceChains(): Promise<string[]> {
    const chains = await this.axelarQuery.getChains();
    return chains.map(chain => chain.name.toLowerCase());
  }

  /**
   * Get supported destination chains for a source chain
   * @param sourceChain Source chain identifier
   * @returns Array of supported destination chain identifiers
   */
  async getSupportedDestinationChains(sourceChain: string): Promise<string[]> {
    const chains = await this.axelarQuery.getChains();
    return chains
      .filter(chain => chain.name.toLowerCase() !== sourceChain.toLowerCase())
      .map(chain => chain.name.toLowerCase());
  }

  /**
   * Get supported tokens for a chain pair
   * @param sourceChain Source chain identifier
   * @param destinationChain Destination chain identifier
   * @returns Array of supported token symbols
   */
  async getSupportedTokens(sourceChain: string, destinationChain: string): Promise<string[]> {
    const assets = await this.axelarQuery.getAssets();
    return assets
      .filter(asset => {
        const sourceInfo = asset.chains.find(c => c.name.toLowerCase() === sourceChain.toLowerCase());
        const destInfo = asset.chains.find(c => c.name.toLowerCase() === destinationChain.toLowerCase());
        return sourceInfo && destInfo;
      })
      .map(asset => asset.symbol);
  }

  /**
   * Prepare a cross-chain transfer
   * @param params Transfer parameters
   * @returns Transfer preparation result with unsigned transaction
   */
  async prepareTransfer(params: TransferParams): Promise<any> {
    const { sourceChain, destinationChain, token, amount, recipient } = params;

    // Validate parameters
    if (!sourceChain || !destinationChain || !token || !amount || !recipient) {
      throw new Error('Missing required parameters');
    }

    // Get token info
    const assets = await this.axelarQuery.getAssets();
    const asset = assets.find(a => a.symbol.toLowerCase() === token.toLowerCase());
    if (!asset) {
      throw new Error(`Token ${token} not supported`);
    }

    // Get chain info
    const sourceChainInfo = asset.chains.find(c => c.name.toLowerCase() === sourceChain.toLowerCase());
    const destChainInfo = asset.chains.find(c => c.name.toLowerCase() === destinationChain.toLowerCase());
    if (!sourceChainInfo || !destChainInfo) {
      throw new Error(`Chain pair ${sourceChain}-${destinationChain} not supported for token ${token}`);
    }

    // Get gateway contract address
    const gatewayAddress = sourceChainInfo.gateway_address;
    if (!gatewayAddress) {
      throw new Error(`Gateway address not found for ${sourceChain}`);
    }

    // Get token contract address
    const tokenAddress = sourceChainInfo.token_address;
    if (!tokenAddress) {
      throw new Error(`Token address not found for ${token} on ${sourceChain}`);
    }

    // Prepare transaction data
    // This will depend on the specific chain and token
    // For EVM chains, we'll prepare an ERC20 approval and a gateway call

    // For this example, we'll assume EVM chains
    // 1. Approve the gateway to spend tokens
    const erc20Interface = new ethers.utils.Interface([
      'function approve(address spender, uint256 amount) external returns (bool)'
    ]);

    const approvalData = erc20Interface.encodeFunctionData('approve', [
      gatewayAddress,
      ethers.utils.parseUnits(amount.toString(), sourceChainInfo.decimals)
    ]);

    const approvalTx = {
      to: tokenAddress,
      data: approvalData,
      value: '0x0'
    };

    // 2. Call the gateway to initiate the transfer
    const gatewayInterface = new ethers.utils.Interface([
      'function sendToken(string destinationChain, string destinationAddress, string symbol, uint256 amount) external'
    ]);

    const gatewayData = gatewayInterface.encodeFunctionData('sendToken', [
      destChainInfo.name,
      recipient,
      asset.symbol,
      ethers.utils.parseUnits(amount.toString(), sourceChainInfo.decimals)
    ]);

    const gatewayTx = {
      to: gatewayAddress,
      data: gatewayData,
      value: '0x0'
    };

    return {
      transactions: [approvalTx, gatewayTx],
      transferId: null, // Will be determined after transaction is submitted
      estimatedFee: await this.estimateFee(sourceChain, destinationChain, token, amount)
    };
  }

  /**
   * Complete a transfer (if needed)
   * @param transferId Transfer identifier
   * @param params Additional parameters for completion
   * @returns Completion result
   */
  async completeTransfer(transferId: string, params?: any): Promise<any> {
    // For Axelar, most transfers complete automatically
    // But we can check if manual execution is needed
    const status = await this.getTransferStatus(transferId);

    if (status.status === 'pending_execution') {
      // Manual execution needed
      const txHash = await this.axelarGMPRecovery.execute(transferId);
      return { txHash };
    }

    return { message: 'No manual execution needed' };
  }

  /**
   * Get transfer status
   * @param transferId Transfer identifier
   * @returns Transfer status information
   */
  async getTransferStatus(transferId: string): Promise<TransferStatus> {
    try {
      const txStatus = await this.axelarQuery.getGMPStatus(transferId);

      let status: TransferStatus['status'];
      switch (txStatus.status) {
        case 'executed':
          status = 'completed';
          break;
        case 'executing':
          status = 'in_progress';
          break;
        case 'approved':
          status = 'pending_execution';
          break;
        case 'error':
          status = 'failed';
          break;
        default:
          status = 'pending';
      }

      return {
        transferId,
        status,
        sourceChain: txStatus.source_chain,
        destinationChain: txStatus.destination_chain,
        sourceTransaction: txStatus.source_tx_hash,
        destinationTransaction: txStatus.destination_tx_hash,
        error: txStatus.error_message || null
      };
    } catch (error) {
      console.error('Error getting transfer status:', error);
      return {
        transferId,
        status: 'unknown',
        error: error.message
      };
    }
  }

  /**
   * Estimate transfer fee
   * @param sourceChain Source chain identifier
   * @param destinationChain Destination chain identifier
   * @param token Token symbol
   * @param amount Transfer amount
   * @returns Estimated fee information
   */
  async estimateFee(sourceChain: string, destinationChain: string, token: string, amount: number): Promise<any> {
    try {
      const fee = await this.axelarQuery.estimateGasFee(
        sourceChain,
        destinationChain,
        token
      );

      return {
        fee: fee.toString(),
        token: 'native', // Fee is paid in native token of source chain
        gasLimit: fee.gasLimit?.toString() || null
      };
    } catch (error) {
      console.error('Error estimating fee:', error);
      throw new Error(`Failed to estimate fee: ${error.message}`);
    }
  }
}

Step 2: Create Package Configuration

Location: /packages/bridges/axelar/

1. Create package.json: Define package metadata, dependencies, and scripts

2. Set Up TypeScript Configuration: Create tsconfig.json

3. Add Build Scripts: Configure build process

// Example: /packages/bridges/axelar/package.json
{
  "name": "@juliaos/bridge-axelar",
  "version": "0.1.0",
  "description": "Axelar bridge integration for JuliaOS",
  "main": "dist/index.js",
  "types": "dist/index.d.ts",
  "scripts": {
    "build": "tsc",
    "test": "jest",
    "lint": "eslint src --ext .ts"
  },
  "dependencies": {
    "@axelar-network/axelarjs-sdk": "^0.12.6",
    "@juliaos/bridge-core": "^0.1.0",
    "ethers": "^5.7.2"
  },
  "devDependencies": {
    "@types/jest": "^29.5.0",
    "@types/node": "^18.15.11",
    "eslint": "^8.38.0",
    "jest": "^29.5.0",
    "ts-jest": "^29.1.0",
    "typescript": "^5.0.4"
  }
}

Step 3: Integrate into Framework

Location: /packages/framework/src/bridge.ts or similar.

1. Import Bridge Provider: Add import for your new bridge provider

2. Update Bridge Registry: Register your bridge provider

// In /packages/framework/src/bridge.ts
import { AxelarBridge } from '@juliaos/bridge-axelar';

// Update the bridge registry
const BRIDGE_PROVIDERS = {
  wormhole: (config) => new WormholeBridge(config),
  relay: (config) => new RelayBridge(config),
  // Add your new bridge
  axelar: (config) => new AxelarBridge(config)
};

// Update the Bridge class
export class Bridge {
  // ...

  /**
   * Get supported bridges
   * @returns Array of supported bridge identifiers
   */
  async getSupportedBridges(): Promise<string[]> {
    const result = await this.bridge.execute('bridges.get_supported_bridges');
    return result.data.bridges;
  }

  // ...
}

Step 4: Integrate into Backend

Location: /julia/src/Bridge.jl or similar.

1. Update Supported Bridges: Add your bridge to the list of supported bridges

2. Add Command Handlers: Implement command handlers for your bridge

# In /julia/src/Bridge.jl

# Update supported bridges
const SUPPORTED_BRIDGES = ["wormhole", "relay", "axelar"]

# Add command handlers for the new bridge
function handle_axelar_bridge_command(command::String, params::Dict)
    if command == "bridges.axelar.get_supported_chains"
        # Implementation
        return success_response(Dict("chains" => ["ethereum", "polygon", "avalanche", "fantom", "arbitrum", "optimism", "binance"]))
    elseif command == "bridges.axelar.get_supported_tokens"
        # Implementation
        return success_response(Dict("tokens" => ["USDC", "USDT", "ETH", "WBTC", "DAI"]))
    elseif command == "bridges.axelar.prepare_transfer"
        # Implementation
        # ...
    elseif command == "bridges.axelar.complete_transfer"
        # Implementation
        # ...
    elseif command == "bridges.axelar.get_transfer_status"
        # Implementation
        # ...
    else
        return error_response("Unknown command: $command")
    end
end

# Register the command handler
BRIDGE_COMMAND_HANDLERS["axelar"] = handle_axelar_bridge_command

Step 5: Update CLI Interface

Location: /packages/cli/src/menus/bridges.js or similar.

// Add your bridge to the bridge selection menu
const bridgeOptions = [
  { name: 'Wormhole', value: 'wormhole' },
  { name: 'Relay Bridge', value: 'relay' },
  // Add your new bridge
  { name: 'Axelar', value: 'axelar' },
];

// Add bridge-specific prompts if needed
const getBridgePrompts = (bridge) => {
  switch (bridge) {
    // Existing cases...

    case 'axelar':
      return [
        {
          type: 'list',
          name: 'environment',
          message: 'Select environment:',
          choices: [
            { name: 'Mainnet', value: 'mainnet' },
            { name: 'Testnet', value: 'testnet' },
          ],
          default: 'mainnet',
        },
      ];

    // Default case...
  }
};

Step 6: Update Python Wrapper

Location: /packages/python-wrapper/juliaos/bridges.py or similar.

from typing import List, Dict, Any, Optional
from .client import JuliaOS

class Bridges:
    """Interface for working with cross-chain bridges."""

    def __init__(self, client: JuliaOS):
        self.client = client

    async def get_supported_bridges(self) -> List[str]:
        """Get supported bridge protocols.

        Returns:
            List of supported bridge identifiers
        """
        result = await self.client.bridge.execute("bridges.get_supported_bridges")
        return result["bridges"]

    # Add bridge-specific methods if needed
    async def get_axelar_supported_chains(self) -> List[str]:
        """Get chains supported by the Axelar bridge.

        Returns:
            List of supported chain identifiers
        """
        result = await self.client.bridge.execute("bridges.axelar.get_supported_chains")
        return result["chains"]

Step 7: Add Tests

1. Unit Tests: Test the bridge provider implementation

// In /packages/bridges/axelar/tests/axelar.test.ts
import { AxelarBridge } from '../src';

describe('AxelarBridge', () => {
  let bridge: AxelarBridge;

  beforeAll(() => {
    bridge = new AxelarBridge({
      environment: 'testnet'
    });
  });

  it('should get supported source chains', async () => {
    const chains = await bridge.getSupportedSourceChains();
    expect(chains).toContain('ethereum');
    expect(chains).toContain('polygon');
  });

  it('should get supported destination chains', async () => {
    const chains = await bridge.getSupportedDestinationChains('ethereum');
    expect(chains).toContain('polygon');
    expect(chains).not.toContain('ethereum');
  });

  it('should get supported tokens', async () => {
    const tokens = await bridge.getSupportedTokens('ethereum', 'polygon');
    expect(tokens).toContain('USDC');
  });

  it('should prepare a transfer', async () => {
    const result = await bridge.prepareTransfer({
      sourceChain: 'ethereum',
      destinationChain: 'polygon',
      token: 'USDC',
      amount: 100,
      recipient: '0x1234...'
    });

    expect(result.transactions).toBeDefined();
    expect(result.transactions.length).toBe(2);  // Approval and transfer
    expect(result.estimatedFee).toBeDefined();
  });

  // Additional tests for other methods
});

1. Integration Tests: Test the bridge through the framework

// In /packages/framework/tests/bridge.test.ts
describe('Bridge - Axelar', () => {
  let bridge: JuliaBridge;
  let bridges: Bridges;

  beforeAll(async () => {
    bridge = new JuliaBridge({ host: 'localhost', port: 8052 });
    await bridge.initialize();
    bridges = new Bridges(bridge);
  });

  afterAll(async () => {
    await bridge.disconnect();
  });

  it('should list Axelar as a supported bridge', async () => {
    const supportedBridges = await bridges.getSupportedBridges();
    expect(supportedBridges).toContain('axelar');
  });

  it('should get supported chains for Axelar', async () => {
    const supportedChains = await bridges.getSupportedChains('axelar');
    expect(supportedChains).toContain('ethereum');
    expect(supportedChains).toContain('polygon');
  });

  it('should prepare a transfer using Axelar', async () => {
    const transferResult = await bridges.prepareTransfer({
      sourceChain: 'ethereum',
      destinationChain: 'polygon',
      token: 'USDC',
      amount: '100.0',
      recipient: '0x1234...',
      bridge: 'axelar'
    });

    expect(transferResult).toBeDefined();
    expect(transferResult.transactions).toBeDefined();
  });
});

Best Practices for Bridge Integration

1. Security First: Implement thorough validation and error handling

2. Comprehensive Testing: Test all aspects of the bridge functionality

3. Clear Documentation: Document the bridge's capabilities, limitations, and usage

4. Error Handling: Provide meaningful error messages and recovery mechanisms

5. Fee Estimation: Accurately estimate fees for cross-chain transfers

6. Status Tracking: Implement robust status tracking for transfers

7. Timeout Handling: Handle timeouts and network issues gracefully

8. Logging: Log important events and errors for debugging

9. Configuration Options: Allow customization of bridge parameters

10. Fallback Mechanisms: Implement fallback mechanisms for failed transfers

Adding a New Wallet Integration

JuliaOS supports various wallet types for managing private keys and signing transactions. This section provides a detailed guide on implementing new wallet integrations.

Step 1: Implement Wallet Adapter (Node.js/TypeScript)

Location: Create a new directory in /packages/wallets/ (e.g., /packages/wallets/ledger).

1. Define Wallet Interface: Create a class that implements the common wallet adapter interface

2. Implement Wallet-Specific Logic: Add methods for connecting to the wallet and performing operations

3. Handle Error Cases: Implement comprehensive error handling

// Example: /packages/wallets/ledger/src/index.ts
import { ethers } from 'ethers';
import TransportWebUSB from '@ledgerhq/hw-transport-webusb';
import Eth from '@ledgerhq/hw-app-eth';
import { WalletAdapter, WalletConfig, WalletConnectionParams } from '@juliaos/wallet-core';

export interface LedgerWalletConfig extends WalletConfig {
  derivationPath?: string;
}

export interface LedgerConnectionParams extends WalletConnectionParams {
  derivationPath?: string;
}

/**
 * Ledger Hardware Wallet Adapter implementation
 */
export class LedgerWallet implements WalletAdapter {
  private transport: any;
  private eth: any;
  private address: string | null = null;
  private derivationPath: string;
  private connected: boolean = false;

  /**
   * Create a new Ledger wallet adapter
   * @param config Wallet configuration
   */
  constructor(config: LedgerWalletConfig = {}) {
    this.derivationPath = config.derivationPath || "m/44'/60'/0'/0/0";
  }

  /**
   * Get wallet type identifier
   * @returns Wallet type string
   */
  getType(): string {
    return 'ledger';
  }

  /**
   * Check if wallet is connected
   * @returns True if wallet is connected
   */
  isConnected(): boolean {
    return this.connected && !!this.address;
  }

  /**
   * Connect to the wallet
   * @param params Connection parameters
   * @returns Connection result with address
   */
  async connect(params: LedgerConnectionParams = {}): Promise<{ address: string }> {
    try {
      // Use provided derivation path or default
      this.derivationPath = params.derivationPath || this.derivationPath;

      // Connect to Ledger device via WebUSB
      this.transport = await TransportWebUSB.create();
      this.eth = new Eth(this.transport);

      // Get Ethereum address from device
      const result = await this.eth.getAddress(this.derivationPath);
      this.address = ethers.utils.getAddress(result.address); // Ensure checksum address
      this.connected = true;

      return { address: this.address };
    } catch (error) {
      console.error('Error connecting to Ledger:', error);
      throw new Error(`Failed to connect to Ledger: ${error.message}`);
    }
  }

  /**
   * Disconnect from the wallet
   */
  async disconnect(): Promise<void> {
    if (this.transport) {
      await this.transport.close();
      this.transport = null;
    }

    this.eth = null;
    this.address = null;
    this.connected = false;
  }

  /**
   * Get connected wallet address
   * @returns Wallet address or null if not connected
   */
  getAddress(): string | null {
    return this.address;
  }

  /**
   * Sign a message with the wallet
   * @param message Message to sign
   * @returns Signature
   */
  async signMessage(message: string): Promise<string> {
    if (!this.isConnected()) {
      throw new Error('Wallet not connected');
    }

    try {
      // Convert message to hex if it's not already
      const messageHex = ethers.utils.isHexString(message)
        ? message
        : ethers.utils.hexlify(ethers.utils.toUtf8Bytes(message));

      // Sign message with Ledger
      const result = await this.eth.signPersonalMessage(
        this.derivationPath,
        messageHex.substring(2) // Remove '0x' prefix
      );

      // Convert signature to Ethereum format
      const v = parseInt(result.v, 16);
      const signature = ethers.utils.joinSignature({
        r: '0x' + result.r,
        s: '0x' + result.s,
        v
      });

      return signature;
    } catch (error) {
      console.error('Error signing message with Ledger:', error);
      throw new Error(`Failed to sign message: ${error.message}`);
    }
  }

  /**
   * Sign a transaction with the wallet
   * @param transaction Transaction to sign
   * @returns Signed transaction
   */
  async signTransaction(transaction: ethers.providers.TransactionRequest): Promise<string> {
    if (!this.isConnected()) {
      throw new Error('Wallet not connected');
    }

    try {
      // Ensure all transaction fields are properly formatted
      const tx = {
        to: transaction.to,
        value: transaction.value ? ethers.utils.hexValue(transaction.value) : '0x0',
        data: transaction.data || '0x',
        gasLimit: transaction.gasLimit ? ethers.utils.hexValue(transaction.gasLimit) : undefined,
        gasPrice: transaction.gasPrice ? ethers.utils.hexValue(transaction.gasPrice) : undefined,
        nonce: transaction.nonce ? ethers.utils.hexValue(transaction.nonce) : undefined,
        chainId: transaction.chainId || 1
      };

      // Sign transaction with Ledger
      const serializedTx = ethers.utils.serializeTransaction(tx);
      const result = await this.eth.signTransaction(
        this.derivationPath,
        serializedTx.substring(2) // Remove '0x' prefix
      );

      // Combine signature with transaction
      const signature = {
        r: '0x' + result.r,
        s: '0x' + result.s,
        v: parseInt(result.v, 16)
      };

      const signedTx = ethers.utils.serializeTransaction(tx, signature);
      return signedTx;
    } catch (error) {
      console.error('Error signing transaction with Ledger:', error);
      throw new Error(`Failed to sign transaction: ${error.message}`);
    }
  }

  /**
   * Send a transaction using the wallet
   * @param transaction Transaction to send
   * @param provider Ethereum provider to use for sending
   * @returns Transaction hash
   */
  async sendTransaction(
    transaction: ethers.providers.TransactionRequest,
    provider: ethers.providers.Provider
  ): Promise<string> {
    if (!this.isConnected()) {
      throw new Error('Wallet not connected');
    }

    try {
      // Ensure transaction has all required fields
      if (!transaction.to) {
        throw new Error('Transaction must specify a recipient (to)');
      }

      // Get the current nonce if not provided
      if (transaction.nonce === undefined) {
        transaction.nonce = await provider.getTransactionCount(this.address!);
      }

      // Get the chain ID if not provided
      if (transaction.chainId === undefined) {
        const network = await provider.getNetwork();
        transaction.chainId = network.chainId;
      }

      // Sign the transaction
      const signedTx = await this.signTransaction(transaction);

      // Send the signed transaction
      const tx = await provider.sendTransaction(signedTx);
      return tx.hash;
    } catch (error) {
      console.error('Error sending transaction with Ledger:', error);
      throw new Error(`Failed to send transaction: ${error.message}`);
    }
  }

  /**
   * Get wallet capabilities
   * @returns Object describing wallet capabilities
   */
  getCapabilities(): Record<string, boolean> {
    return {
      signMessage: true,
      signTransaction: true,
      signTypedData: false, // Ledger doesn't support EIP-712 in all models
      multipleAccounts: true,
      multipleNetworks: true
    };
  }
}

Step 2: Create Package Configuration

Location: /packages/wallets/ledger/

1. Create package.json: Define package metadata, dependencies, and scripts

2. Set Up TypeScript Configuration: Create tsconfig.json

3. Add Build Scripts: Configure build process

// Example: /packages/wallets/ledger/package.json
{
  "name": "@juliaos/wallet-ledger",
  "version": "0.1.0",
  "description": "Ledger hardware wallet integration for JuliaOS",
  "main": "dist/index.js",
  "types": "dist/index.d.ts",
  "scripts": {
    "build": "tsc",
    "test": "jest",
    "lint": "eslint src --ext .ts"
  },
  "dependencies": {
    "@juliaos/wallet-core": "^0.1.0",
    "@ledgerhq/hw-app-eth": "^6.30.3",
    "@ledgerhq/hw-transport-webusb": "^6.27.12",
    "ethers": "^5.7.2"
  },
  "devDependencies": {
    "@types/jest": "^29.5.0",
    "@types/node": "^18.15.11",
    "eslint": "^8.38.0",
    "jest": "^29.5.0",
    "ts-jest": "^29.1.0",
    "typescript": "^5.0.4"
  }
}

Step 3: Integrate into Wallet Manager

Location: /packages/wallets/src/walletManager.ts or similar.

1. Import Wallet Adapter: Add import for your new wallet adapter

2. Update Wallet Registry: Register your wallet adapter

// In /packages/wallets/src/walletManager.ts
import { LedgerWallet } from '@juliaos/wallet-ledger';

// Update the wallet registry
const WALLET_ADAPTERS = {
  metamask: () => new MetaMaskWallet(),
  walletconnect: (config) => new WalletConnectWallet(config),
  // Add your new wallet
  ledger: (config) => new LedgerWallet(config)
};

// Update the WalletManager class
export class WalletManager {
  // ...

  /**
   * Get supported wallet types
   * @returns Array of supported wallet type identifiers
   */
  getSupportedWalletTypes(): string[] {
    return Object.keys(WALLET_ADAPTERS);
  }

  /**
   * Connect to a wallet
   * @param walletType Wallet type identifier
   * @param params Connection parameters
   * @returns Connected wallet adapter
   */
  async connectWallet(walletType: string, params: any = {}): Promise<WalletAdapter> {
    if (!WALLET_ADAPTERS[walletType]) {
      throw new Error(`Unsupported wallet type: ${walletType}`);
    }

    const adapter = WALLET_ADAPTERS[walletType](params);
    await adapter.connect(params);

    this.currentWallet = adapter;
    return adapter;
  }

  // ...
}

Step 4: Update CLI Interface

Location: /packages/cli/src/menus/wallets.js or similar.

// Add your wallet to the wallet selection menu
const walletOptions = [
  { name: 'MetaMask', value: 'metamask' },
  { name: 'WalletConnect', value: 'walletconnect' },
  // Add your new wallet
  { name: 'Ledger Hardware Wallet', value: 'ledger' },
];

// Add wallet-specific prompts if needed
const getWalletPrompts = (wallet) => {
  switch (wallet) {
    // Existing cases...

    case 'ledger':
      return [
        {
          type: 'input',
          name: 'derivationPath',
          message: 'Enter derivation path (leave empty for default):',
          default: "m/44'/60'/0'/0/0",
        },
      ];

    // Default case...
  }
};

// Implement wallet connection logic
const connectWallet = async (walletType, params) => {
  try {
    console.log(`Connecting to ${walletType} wallet...`);

    if (walletType === 'ledger') {
      console.log('Please connect your Ledger device and open the Ethereum app.');
      console.log('Make sure your device is unlocked and the Ethereum app is open.');
    }

    const wallet = await bridge.execute('wallets.connect', {
      wallet_type: walletType,
      params
    });

    console.log(`Connected to wallet: ${wallet.data.address}`);
    return wallet.data;
  } catch (error) {
    console.error(`Error connecting to wallet: ${error.message}`);
    throw error;
  }
};

Step 5: Update Python Wrapper

Location: /packages/python-wrapper/juliaos/wallets.py or similar.

from typing import List, Dict, Any, Optional
from .client import JuliaOS

class Wallets:
    """Interface for working with wallets."""

    def __init__(self, client: JuliaOS):
        self.client = client

    async def get_supported_wallet_types(self) -> List[str]:
        """Get supported wallet types.

        Returns:
            List of supported wallet type identifiers
        """
        result = await self.client.bridge.execute("wallets.get_supported_types")
        return result["wallet_types"]

    async def connect_wallet(self, wallet_type: str, params: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
        """Connect to a wallet.

        Args:
            wallet_type: Wallet type identifier
            params: Connection parameters

        Returns:
            Connected wallet information
        """
        result = await self.client.bridge.execute("wallets.connect", {
            "wallet_type": wallet_type,
            "params": params or {}
        })
        return result

    # Add wallet-specific methods if needed
    async def connect_ledger(self, derivation_path: Optional[str] = None) -> Dict[str, Any]:
        """Connect to a Ledger hardware wallet.

        Args:
            derivation_path: Custom derivation path (optional)

        Returns:
            Connected wallet information
        """
        params = {}
        if derivation_path:
            params["derivation_path"] = derivation_path

        return await self.connect_wallet("ledger", params)

Step 6: Add Tests

1. Unit Tests: Test the wallet adapter implementation

// In /packages/wallets/ledger/tests/ledger.test.ts
import { LedgerWallet } from '../src';

// Note: Testing hardware wallets is challenging and may require mocks
// This is a simplified example
describe('LedgerWallet', () => {
  let wallet: LedgerWallet;

  beforeAll(() => {
    wallet = new LedgerWallet();
  });

  it('should return correct wallet type', () => {
    expect(wallet.getType()).toBe('ledger');
  });

  it('should report not connected initially', () => {
    expect(wallet.isConnected()).toBe(false);
  });

  it('should report correct capabilities', () => {
    const capabilities = wallet.getCapabilities();
    expect(capabilities.signMessage).toBe(true);
    expect(capabilities.signTransaction).toBe(true);
    expect(capabilities.multipleAccounts).toBe(true);
  });

  // For actual connection tests, you would need to mock the Ledger transport
  // or use a testing environment that can simulate hardware wallet interactions
});

1. Integration Tests: Test the wallet through the framework

// In /packages/framework/tests/wallet.test.ts
describe('WalletManager - Ledger', () => {
  let bridge: JuliaBridge;
  let walletManager: WalletManager;

  beforeAll(async () => {
    bridge = new JuliaBridge({ host: 'localhost', port: 8052 });
    await bridge.initialize();
    walletManager = new WalletManager(bridge);
  });

  afterAll(async () => {
    await bridge.disconnect();
  });

  it('should list Ledger as a supported wallet type', async () => {
    const supportedTypes = walletManager.getSupportedWalletTypes();
    expect(supportedTypes).toContain('ledger');
  });

  // For actual connection tests, you would need to mock the hardware wallet
  // or use a testing environment that can simulate hardware wallet interactions
});

Step 7: Add Documentation

Location: /docs/gitbook/technical/features/wallets.md or similar.

## Ledger Hardware Wallet

JuliaOS supports Ledger hardware wallets for secure key management and transaction signing.

### Features

- Secure private key storage on the hardware device
- Support for multiple accounts via different derivation paths
- Transaction signing without exposing private keys
- Message signing for authentication

### Requirements

- Ledger Nano S, Nano X, or Nano S Plus device
- Latest firmware installed on the device
- Ethereum app installed on the device
- WebUSB-compatible browser (Chrome, Edge, Opera, Brave)

### Usage

```javascript
// Connect to a Ledger wallet
const wallet = await juliaos.wallets.connectWallet('ledger', {
  derivationPath: "m/44'/60'/0'/0/0" // Optional, defaults to this path
});

// Sign a transaction
const txHash = await wallet.sendTransaction({
  to: '0x1234...',
  value: ethers.utils.parseEther('0.1'),
  data: '0x'
});

Supported Networks

Ledger wallets can be used with any EVM-compatible network supported by JuliaOS, including:

• Ethereum (Mainnet, Sepolia, Goerli)

• Polygon

• Arbitrum

• Optimism

• Avalanche C-Chain

• Binance Smart Chain

• And more

Security Considerations

• Always verify transaction details on the Ledger device screen before confirming

• Ensure you're using the latest firmware and Ethereum app version

• Be cautious of phishing attempts and always verify the authenticity of the JuliaOS application

#### Best Practices for Wallet Integration

1. **Security First**: Implement thorough validation and error handling
2. **User Experience**: Provide clear instructions and feedback during wallet connection
3. **Error Handling**: Provide meaningful error messages for common issues
4. **Comprehensive Testing**: Test all wallet operations thoroughly
5. **Documentation**: Document the wallet's capabilities, limitations, and usage
6. **Chain Support**: Clearly document which chains are supported by the wallet
7. **Transaction Validation**: Implement proper transaction validation before signing
8. **Privacy**: Respect user privacy and only request necessary permissions
9. **Fallback Mechanisms**: Provide fallback options if the primary connection method fails
10. **Disconnection Handling**: Properly handle wallet disconnection events