Atomic Agents Project Structure: This skill should be used when the user asks to "create project structure", "organize atomic agents project", "pyproject.toml", "project layout", "directory structure", or needs guidance on organizing files, configuring dependencies, and structuring Atomic Agents applications for maintainability.
Installation
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skills listSkill Instructions
description: This skill should be used when the user asks to "create project structure", "organize atomic agents project", "pyproject.toml", "project layout", "directory structure", or needs guidance on organizing files, configuring dependencies, and structuring Atomic Agents applications for maintainability.
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
| Component | File Pattern | Class Pattern |
|---|---|---|
| Agents | *_agent.py | *Agent |
| Tools | *_tool.py | *Tool |
| Schemas | schemas.py or *.py | *Schema |
| Providers | *_provider.py | *Provider |
| Config | config.py | Config, *Config |
| Services | *_service.py | *Service |
Best Practices
- One agent per file - Easier to maintain and test
- Shared schemas in schemas.py - Or schemas/ directory for many
- Factory functions -
create_*_agent()for configurable agents - Type hints everywhere - IDE support and documentation
- Docstrings - Document purpose of each module
- Tests alongside code - tests/ directory mirroring src
- Rich for output - Consistent, beautiful terminal output
References
See references/ for:
testing-structure.md- Test organization patternsapi-structure.md- FastAPI integration layout
See examples/ for:
minimal-project/- Simplest structurefull-project/- Complete structure template
More by BrainBlend-AI
View allRelease a new version of atomic-agents to PyPI and GitHub. Use when the user asks to "release", "publish", "deploy", or "bump version" for atomic-agents.
Atomic Agents Context Providers: This skill should be used when the user asks to "create context provider", "dynamic context", "inject context", "BaseDynamicContextProvider", "share data between agents", or needs guidance on context providers, dynamic prompt injection, and sharing information across agents in Atomic Agents applications.
Atomic Agents Schema Design: This skill should be used when the user asks to "create a schema", "define input/output", "add fields", "validate data", "Pydantic schema", "BaseIOSchema", or needs guidance on schema design patterns, field definitions, validators, and type constraints for Atomic Agents applications.
Atomic Agents Tool Development: This skill should be used when the user asks to "create a tool", "implement BaseTool", "add tool to agent", "tool orchestration", "external API tool", or needs guidance on tool development, tool configuration, error handling, and integrating tools with agents in Atomic Agents applications.
