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pydantic/monty · source

Snapshot 0 · 2026-11-04T12:47:27Z · Rust · MIT

GitHub description at capture

A secure Python sandbox, written in Rust, for code written by AI.

README at capture

<div align="center">
  <h1>Monty</h1>
</div>
<div align="center">
  <h3>A secure Python sandbox, written in Rust, for code written by AI.</h3>
</div>
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______________________________________________________________________

Monty avoids the latency, complexity and cost of a container based sandbox for running LLM generated code.
It comes in two forms: **OSS Monty**, the MIT licensed Python 3.14 sandbox you install as a package, and
[**Full Monty**](https://pydantic.dev/docs/monty/commercial-support/server/), the commercial server that runs the same sandbox behind a WebSocket as a service.

A new OSS Monty sandbox takes under **1ms** from a running pool (Full Monty: about **2ms**)
[compared to](https://pydantic.dev/docs/monty/reference/alternatives/) around **1500ms** for a sandbox service.

Filesystem, environment variables and network do not exist inside the sandbox: it reaches the host only through the
functions and mounts you pass in.

**Documentation: [pydantic.dev/docs/monty](https://pydantic.dev/docs/monty/)**

## Install

```bash
uv add pydantic-monty        # Python
npm install @pydantic/monty  # JavaScript / TypeScript
cargo add monty              # Rust
```

The commercial [Full Monty](https://pydantic.dev/docs/monty/commercial-support/server/) runs the same workers as a container
image.

## Example

The `code` string is what a model writes when asked how long a bar of chocolate could power a lightbulb:

```python
from pydantic_monty import Monty

code = """
kcal = nutrition('chocolate bar')['kcal']
hours = kcal * 4184 / (bulb_watts * 3600)
print(f'a chocolate bar powers a {bulb_watts} W bulb for {hours:.1f} hours')
"""

with Monty() as pool:
    with pool.checkout() as session:
        session.feed_run(
            code,
            inputs={'bulb_watts': 10},
            external_lookup={'nutrition': lambda food: {'kcal': 230}},
        )
        #> a chocolate bar powers a 10 W bulb for 26.7 hours
```

`nutrition` ran on the host and the sandbox saw only its return value.

## Documentation

- [Introduction](https://pydantic.dev/docs/monty/) with the latency measurements
- [Comparison to alternatives](https://pydantic.dev/docs/monty/reference/alternatives/): Docker, Pyodide, WASI,
    sandboxing services
- Getting started with [Python](https://pydantic.dev/docs/monty/quickstart/python/),
    [JavaScript](https://pydantic.dev/docs/monty/quickstart/javascript/) or
    [Rust](https://pydantic.dev/docs/monty/quickstart/rust/)
- [Security model](https://pydantic.dev/docs/monty/concepts/security/), [resource
    limits](https://pydantic.dev/docs/monty/concepts/resource-limits/),
    [snapshots](https://pydantic.dev/docs/monty/concepts/snapshots/), [the Python
    subset](https://pydantic.dev/docs/monty/limitations/)
- [`docs/`](./docs): the source of the documentation site

Monty runs [Code Mode](https://pydantic.dev/docs/ai/harness/code-mode/) in [Pydantic
AI](https://github.com/pydantic/pydantic-ai).
Community bindings: [gomonty](https://github.com/ewhauser/gomonty/) (Go) and
[dart_monty](https://github.com/runyaga/dart_monty) (Dart / Flutter).

## Part of the Pydantic Stack

The Pydantic Stack is everything you need to ship production-grade AI agents:

- [Pydantic AI](https://pydantic.dev/pydantic-ai?utm_source=github&utm_medium=readme&utm_campaign=monty) - Type-safe
    agent framework
- [Pydantic Logfire](https://pydantic.dev/logfire?utm_source=github&utm_medium=readme&utm_campaign=monty) - AI-first,
    full-stack observability
- [Logfire AI Gateway](https://pydantic.dev/ai-gateway?utm_source=github&utm_medium=readme&utm_campaign=monty) - Unified
    LLM proxy