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<h1 align="center">Pydantic Deep Agents</h1>
<p align="center">
<em>Deep Agent Framework, the Pydantic AI way</em>
</p>
<p align="center">
<a href="https://github.com/vstorm-co/pydantic-deepagents/actions/workflows/ci.yml"><img src="https://github.com/vstorm-co/pydantic-deepagents/actions/workflows/ci.yml/badge.svg" alt="CI"></a>
<a href="https://codecov.io/gh/vstorm-co/pydantic-deepagents"><img src="https://img.shields.io/badge/coverage-100%25-brightgreen" alt="Coverage"></a>
<a href="https://pypi.org/project/pydantic-deep/"><img src="https://img.shields.io/pypi/v/pydantic-deep.svg" alt="PyPI"></a>
<a href="https://www.python.org/"><img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue" alt="Python"></a>
<a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/license-MIT-green" alt="License"></a>
</p>
---
**Pydantic Deep Agents** is a Python framework for building autonomous AI agents with planning, filesystem operations, subagent delegation, and skills. Built on [Pydantic AI](https://ai.pydantic.dev/).
Think of it as the building blocks for creating your own [Claude Code](https://claude.ai/code), [Manus](https://manus.im/), or [Devin](https://devin.ai/)-style agents - but open source and self-hosted.
## Why use Pydantic Deep Agents?
1. **Built on Pydantic AI**: Leverages the same ergonomic design that made FastAPI successful - type hints, async/await, and familiar Python patterns.
2. **Production Ready**: 100% test coverage, strict typing with Pyright + MyPy, and battle-tested in real applications.
3. **Modular Architecture**: Use the full framework or cherry-pick components. Each capability is an independent package you can use standalone.
4. **Secure Execution**: Docker sandbox for isolated code execution, permission controls, and human-in-the-loop approval workflows.
## Hello World Example
```python
import asyncio
from pydantic_deep import create_deep_agent, DeepAgentDeps, StateBackend
async def main():
# Create a deep agent with all capabilities
agent = create_deep_agent(
model="openai:gpt-4.1",
instructions="You are a helpful coding assistant.",
)
# Create dependencies with in-memory storage
deps = DeepAgentDeps(backend=StateBackend())
# Run the agent
result = await agent.run(
"Create a Python function that calculates fibonacci numbers",
deps=deps,
)
print(result.output)
asyncio.run(main())
```
## Tools & Dependency Injection Example
```python
from pydantic_ai import RunContext
from pydantic_deep import create_deep_agent, DeepAgentDeps
# Define a custom tool
async def get_weather(
ctx: RunContext[DeepAgentDeps],
city: str,
) -> str:
"""Get weather for a city."""
# Access dependencies via ctx.deps
return f"Weather in {city}: Sunny, 22°C"
# Create agent with custom tools
agent = create_deep_agent(
tools=[get_weather],
instructions="You can check weather and work with files.",
)
```
## Core Capabilities
| Capability | Description |
|------------|-------------|
| **Planning** | Built-in todo list for task decomposition and progress tracking |
| **Filesystem** | Read, write, edit files with grep and glob support |
| **Subagents** | Delegate specialized tasks to isolated subagents |
| **Skills** | Modular capability packages loaded on-demand |
| **Backends** | StateBackend, LocalBackend, DockerSandbox, CompositeBackend |
| **Summarization** | Automatic context management for long conversations |
## Modular Ecosystem
Pydantic Deep Agents is built from standalone packages you can use independently:
| Package | Description |
|---------|-------------|
| [pydantic-ai-backend](https://github.com/vstorm-co/pydantic-ai-backend) | File storage, Docker sandbox, permission controls |
| [pydantic-ai-todo](https://github.com/vstorm-co/pydantic-ai-todo) | Task planning with PostgreSQL and event streaming |
| [subagents-pydantic-ai](https://github.com/vstorm-co/subagents-pydantic-ai) | Multi-agent orchestration |
| [summarization-pydantic-ai](https://github.com/vstorm-co/summarization-pydantic-ai) | Context management processors |
## Installation
```bash
pip install pydantic-deep
```
With Docker sandbox support:
```bash
pip install pydantic-deep[sandbox]
```
## llms.txt
Pydantic Deep Agents supports the [llms.txt](https://llmstxt.org/) standard. Access documentation at `/llms.txt` for LLM-optimized content.
## Next Steps
- [Installation](installation.md) - Get started in minutes
- [Core Concepts](concepts/index.md) - Learn about agents, backends, and toolsets
- [Examples](examples/index.md) - See pydantic-deep in action
- [API Reference](api/index.md) - Complete API documentation