Atomic Agents Project Structure

Proper project organization is essential for maintainable Atomic Agents applications. Structure scales from simple scripts to complex multi-agent systems.

Project Structure Patterns

Simple Application (1-2 agents)

my_project/
├── pyproject.toml          # Project metadata and dependencies
├── .env                    # Environment variables (API keys)
├── .env.example            # Template for .env
├── .gitignore              # Git ignore patterns
├── README.md               # Documentation
└── my_project/
    ├── __init__.py
    ├── main.py             # Entry point
    ├── config.py           # Configuration
    └── schemas.py          # Input/output schemas

Medium Application (3-5 agents with tools)

my_project/
├── pyproject.toml
├── .env
├── .env.example
├── .gitignore
├── README.md
└── my_project/
    ├── __init__.py
    ├── main.py             # Entry point and orchestration
    ├── config.py           # Configuration
    ├── schemas.py          # Shared schemas
    ├── agents/
    │   ├── __init__.py
    │   ├── query_agent.py  # Agent 1
    │   └── response_agent.py # Agent 2
    └── tools/
        ├── __init__.py
        ├── search_tool.py
        └── calculator_tool.py

Complex Application (multi-agent with services)

my_project/
├── pyproject.toml
├── .env
├── .env.example
├── .gitignore
├── README.md
├── tests/
│   ├── __init__.py
│   ├── test_agents.py
│   └── test_tools.py
└── my_project/
    ├── __init__.py
    ├── main.py
    ├── config.py
    ├── agents/
    │   ├── __init__.py
    │   ├── query_agent.py
    │   ├── synthesis_agent.py
    │   └── validation_agent.py
    ├── tools/
    │   ├── __init__.py
    │   └── api_tool.py
    ├── schemas/
    │   ├── __init__.py
    │   ├── inputs.py
    │   └── outputs.py
    ├── services/
    │   ├── __init__.py
    │   ├── database.py
    │   └── external_api.py
    ├── context_providers/
    │   ├── __init__.py
    │   └── rag_provider.py
    └── presentation/
        ├── __init__.py
        └── console.py

pyproject.toml Template

[project]
name = "my-project"
version = "0.1.0"
description = "An Atomic Agents application for [purpose]"
readme = "README.md"
requires-python = ">=3.11"
license = { text = "MIT" }
authors = [{ name = "Your Name", email = "you@example.com" }]

dependencies = [
    "atomic-agents>=1.0.0",
    "instructor>=1.0.0",
    "openai>=1.0.0",
    "python-dotenv>=1.0.0",
    "pydantic>=2.0.0",
    "rich>=13.0.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.0.0",
    "pytest-asyncio>=0.21.0",
    "black>=23.0.0",
    "ruff>=0.1.0",
]

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[tool.hatch.build.targets.wheel]
packages = ["my_project"]

Configuration Pattern

config.py:

import os
from dataclasses import dataclass
from dotenv import load_dotenv

load_dotenv()


def get_api_key() -> str:
    """Get OpenAI API key from environment."""
    key = os.getenv("OPENAI_API_KEY")
    if not key:
        raise ValueError("OPENAI_API_KEY environment variable not set")
    return key


@dataclass
class Config:
    """Application configuration."""

    api_key: str = None
    model: str = "gpt-4o-mini"
    max_tokens: int = 1000
    temperature: float = 0.7

    def __post_init__(self):
        if self.api_key is None:
            self.api_key = get_api_key()


# Global config instance
config = Config()

Environment Variables

.env.example (commit this):

# LLM Provider
OPENAI_API_KEY=sk-your-key-here
# ANTHROPIC_API_KEY=your-key-here

# Application Settings
MODEL=gpt-4o-mini
MAX_TOKENS=1000
TEMPERATURE=0.7

# External Services
# DATABASE_URL=postgresql://...
# REDIS_URL=redis://...

.gitignore additions:

# Environment
.env
.env.local
.env.*.local

# Python
__pycache__/
*.py[cod]
.venv/
venv/

# IDE
.idea/
.vscode/
*.swp

# Testing
.pytest_cache/
.coverage
htmlcov/

Entry Point Pattern

main.py:

"""Main entry point for the application."""

import instructor
import openai
from rich.console import Console

from .config import config
from .agents.query_agent import create_query_agent
from .schemas import UserInput

console = Console()


def main():
    """Run the application."""
    # Initialize client
    client = instructor.from_openai(openai.OpenAI(api_key=config.api_key))

    # Create agent
    agent = create_query_agent(client, config.model)

    # Main loop
    console.print("[bold green]Ready![/bold green]")
    while True:
        try:
            user_input = console.input("[bold blue]You:[/bold blue] ")
            if user_input.lower() in ("exit", "quit"):
                break

            response = agent.run(UserInput(message=user_input))
            console.print(f"[bold green]Agent:[/bold green] {response.message}")

        except KeyboardInterrupt:
            break

    console.print("\n[yellow]Goodbye![/yellow]")


if __name__ == "__main__":
    main()

Agent Module Pattern

agents/query_agent.py:

"""Query processing agent."""

from atomic_agents.agents.base_agent import AtomicAgent, AgentConfig
from atomic_agents.lib.components.system_prompt_generator import SystemPromptGenerator
from atomic_agents.lib.components.chat_history import ChatHistory

from ..schemas import QueryInput, QueryOutput


def create_query_agent(client, model: str) -> AtomicAgent[QueryInput, QueryOutput]:
    """Create and configure the query agent."""
    config = AgentConfig(
        client=client,
        model=model,
        history=ChatHistory(),
        system_prompt_generator=SystemPromptGenerator(
            background=["You are a helpful query processor."],
            steps=["1. Understand the query.", "2. Generate response."],
            output_instructions=["Be concise and helpful."],
        ),
    )
    return AtomicAgent[QueryInput, QueryOutput](config=config)

File Naming Conventions

*_agent.py

*Agent

*_tool.py

*Tool

schemas.py

*.py

*Schema

*_provider.py

*Provider

config.py

Config

*Config

*_service.py

*Service

Best Practices

1. One agent per file - Easier to maintain and test
2. Shared schemas in schemas.py - Or schemas/ directory for many
3. Factory functions -

   create_*_agent()

   for configurable agents
4. Type hints everywhere - IDE support and documentation
5. Docstrings - Document purpose of each module
6. Tests alongside code - tests/ directory mirroring src
7. Rich for output - Consistent, beautiful terminal output

References

See

references/

• testing-structure.md

  - Test organization patterns

• api-structure.md

  - FastAPI integration layout

See

examples/

• minimal-project/

  - Simplest structure

• full-project/

  - Complete structure template