Factory Pattern
The Factory Pattern creates AI agents without specifying their exact classes, providing a unified interface for agent instantiation.
Pattern Overview
This pattern encapsulates agent creation logic, allowing the system to create different types of agents based on input parameters or runtime conditions.
Structure
use std::collections::HashMap;
// Agent trait that all agents implement
pub trait Agent {
fn execute(&self, input: &str) -> String;
fn get_type(&self) -> &str;
}
// Concrete agent implementations
pub struct AnalysisAgent {
name: String,
}
impl Agent for AnalysisAgent {
fn execute(&self, input: &str) -> String {
format!("Analyzing: {}", input)
}
fn get_type(&self) -> &str {
"analysis"
}
}
pub struct OptimizationAgent {
name: String,
}
impl Agent for OptimizationAgent {
fn execute(&self, input: &str) -> String {
format!("Optimizing: {}", input)
}
fn get_type(&self) -> &str {
"optimization"
}
}
// Factory for creating agents
pub struct AgentFactory;
impl AgentFactory {
pub fn create_agent(agent_type: &str, name: &str) -> Option<Box<dyn Agent>> {
match agent_type {
"analysis" => Some(Box::new(AnalysisAgent {
name: name.to_string(),
})),
"optimization" => Some(Box::new(OptimizationAgent {
name: name.to_string(),
})),
_ => None,
}
}
}Usage Example
let agent = AgentFactory::create_agent("analysis", "DataAnalyzer")
.expect("Failed to create agent");
let result = agent.execute("customer behavior data");
println!("{}", result);Benefits
- Decoupling: Separates agent creation from usage
- Extensibility: Easy to add new agent types
- Consistency: Uniform interface for all agent creation
- Flexibility: Runtime agent type selection
Use Cases
- Creating agents based on business requirements
- Loading agent configurations from external sources
- Supporting plugin-based agent architectures
- Managing agent lifecycles in distributed systems