Autonomous Multi-Agent Coding Assistant

How It Works

The system uses multiple AI agents with specialized skills that coordinate through a central orchestrator to solve complex programming tasks. Each agent has a specific role in the workflow:

Code Architecture

Orchestrator Implementation

The Orchestrator is the central component of the system. It initializes all agents, manages the shared memory, and coordinates the workflow. Below is an example of its implementation:

class Orchestrator:
    def __init__(self):
        self.agents = {
            "architect": ArchitectAgent(),
            "coder": CoderAgent(),
            "tester": TesterAgent(),
            "debugger": DebuggerAgent()
        }
        self.shared_memory = SharedMemory()
    
    def process_task(self, task):
        # 1. Architect creates design
        design = self.agents["architect"].design(task)
        self.shared_memory.save("design", design)
        
        # 2. Coder implements design
        code = self.agents["coder"].implement(self.shared_memory.get("design"))
        self.shared_memory.save("code", code)
        
        # 3. Tester verifies implementation
        test_results = self.agents["tester"].test(self.shared_memory.get("code"))
        self.shared_memory.save("test_results", test_results)
        
        # 4. Debugger fixes issues if tests fail
        if not test_results["passed"]:
            fixes = self.agents["debugger"].debug(
                self.shared_memory.get("code"),
                self.shared_memory.get("test_results")
            )
            self.shared_memory.save("code", fixes)
        
        return self.shared_memory.get("code")

Agent Implementations

Each agent has a specific role and is implemented as a separate class. Below are examples of their implementations:

class ArchitectAgent:
    def design(self, task_description):
        """
        Analyze task requirements and create system design.
        """
        requirements = self._extract_requirements(task_description)
        patterns = self._identify_patterns(requirements)
        components = self._design_components(requirements, patterns)
        interfaces = self._define_interfaces(components)
        return {
            "requirements": requirements,
            "patterns": patterns,
            "components": components,
            "interfaces": interfaces
        }

class CoderAgent:
    def implement(self, design):
        """
        Convert design specifications to code implementation.
        """
        implementation_plan = self._create_implementation_plan(design)
        code_files = {}
        for component in design["components"]:
            code_files[component["name"]] = self._implement_component(
                component, design["interfaces"]
            )
        return code_files

class TesterAgent:
    def test(self, code):
        """
        Validate the code by running test cases.
        """
        test_results = self._run_tests(code)
        return test_results

class DebuggerAgent:
    def debug(self, code, test_results):
        """
        Fix issues in the code based on test results.
        """
        fixed_code = self._apply_fixes(code, test_results)
        return fixed_code

Workflow Steps

The workflow of the system is divided into the following steps:

Features & Benefits