semvec/pypi-packages huggingface dataset:
openfoundry 0.1.0
Multi-Agent Orchestration Framework
License: MIT
Requires Python: >=3.12
Keywords: ai, agents, llm, orchestration, multi-agent

# OpenFoundry

Multi-agent orchestration framework for AI applications.

## Overview

OpenFoundry is a framework for building and orchestrating AI agents across the full AI lifecycle:

- **The Forge** - Development & SDLC agents (Architect, Engineer, Quality)
- **The Conveyor** - CI/CD & deployment agents (DevOps, Release)
- **The Shield** - Responsible AI & safety (Guardrails, PII detection)
- **The Watchtower** - Monitoring & observability (OpenTelemetry, Prometheus)

## Features

- Protocol-based agent interfaces (PEP 544)
- Multi-provider LLM support via LiteLLM (OpenAI, Anthropic, Google, Mistral, etc.)
- Async-first architecture for high concurrency
- Structured outputs with Pydantic validation
- DAG-based workflow engine
- Comprehensive guardrails for safe AI usage
- Full observability with OpenTelemetry and Prometheus

## Quick Start

```bash
# Install
pip install openfoundry

# Initialize a new project
openfoundry init

# Start the server
openfoundry serve

# List available agents
openfoundry agent list
```

## Requirements

- Python 3.12+
- API keys for LLM providers (OpenAI, Anthropic, etc.)

## Documentation

See the [docs](./docs) directory for detailed documentation.

## License

MIT
sbox 1.1.0
A simple secret manager with Pydantic model migration support
License: MIT

# sbox
A simple secret manager with Pydantic model migration support

## Key Features
- **Auto-Migration:** If you add or remove fields in your Pydantic model, `sbox` automatically updates your JSON vault.
- **Interactive Mode:** Missing secrets? `sbox` will ask for them in the CLI.
- **Environment Support:** Easily override secrets using Environment Variables.
- **Security:** Automatically sets file permissions to `600` on Linux systems.

## Installation
```bash
pip install sbox
```

## How to use
1. Create `SBox` object:
```python
from sbox import SBox

box = SBox()
```
2. Create Pydantic model:
```python
from sbox import SBox

from pydantic import BaseModel

box = SBox()

class MyModel(BaseModel):
    smth: str
```
3. Parse it and save to file
```python
from sbox import SBox

from pydantic import BaseModel

box = SBox()

class MyModel(BaseModel):
    smth: str

box.parse(MyModel)
box.saveall()
```
4. Get the fields
```python
from sbox import SBox

from pydantic import BaseModel

box = SBox()

class MyModel(BaseModel):
    smth: str

box.parse(MyModel)
box.saveall()

mymodel = box.get_model(MyModel) # Or just box.MyModel
print(f'smth: {mymodel.smth}')
```