belgie 0.29.0

A Javascript Sandbox for Python, powered by Deno

Belgie: A Javascript Sandbox for Python, powered by Deno

Belgie lets you run JavaScript and TypeScript from Python. Deno is bundled — you do not need Node.js or Deno on your PATH.

• Scripts from Python: Run inline or file-based JS/TS with Runtime and Script, sync or async.
• Inline dependencies: Import npm, JSR, and URL modules directly from JS/TS source.
• Isolated packages: Use Environment for lockfiles, custom cache/options, local packages, and commands.
• CLI tools: Run npm binaries (Vite, esbuild, etc.) through Command.
• Simple data bridge: Pass JSON-safe dicts, lists, and primitives across the boundary.
• Pydantic AI: Add belgie as a capability so agents get a run_code tool for sandboxed JS/TS.

Installation

uv add belgie
uvx library-skills install  # optional: install the use-belgie skill for Cursor, Codex, Claude, etc.

Quick Start

import asyncio

from belgie import Runtime, Script

script = Script[[str], str](
    """
import camelcase from "npm:camelcase@8.0.0";

export default function run(input: string): string {
  return camelcase(input);
}
"""
)

async def main() -> None:
    async with Runtime() as run:
        print(await run(script)("foo-bar"))  # prints: fooBar

asyncio.run(main())

Pydantic AI

belgie.ext.pydantic_ai.BelgieCapability is a Pydantic AI capability that gives the agent a run_code tool. The model writes a belgie.Script module and Belgie runs it in the embedded Deno sandbox.

Install the optional extra with uv add "belgie[pydantic-ai]". Set OPENAI_API_KEY, then:

from pydantic_ai import Agent

from belgie.ext.pydantic_ai import BelgieCapability

agent = Agent("openai:gpt-5", capabilities=[BelgieCapability()])

result = agent.run_sync(
    "Use run_code with a TypeScript belgie.Script module that imports npm:camelcase "
    "and returns camelCase('foo-bar').",
)
print(result.output)

See the full runnable project in examples/pydantic-ai.

LangChain

belgie.ext.langchain.BelgieMiddleware is a LangChain agent middleware that gives the agent a run_code tool. The model writes a belgie.Script module and Belgie runs it in the embedded Deno sandbox.

Install the optional extra with uv add "belgie[langchain]". Set OPENAI_API_KEY, then:

from langchain.agents import create_agent

from belgie.ext.langchain import BelgieMiddleware

agent = create_agent(
    model="openai:gpt-5",
    tools=[],
    middleware=[BelgieMiddleware()],
    system_prompt="You can execute JS/TS in a Deno sandbox with run_code.",
)

result = agent.invoke(
    {
        "messages": [
            (
                "user",
                "Use run_code with a TypeScript belgie.Script module that imports npm:camelcase "
                "and returns camelCase('foo-bar').",
            ),
        ],
    },
)
print(result["messages"][-1].content)

See the full runnable project in examples/langchain.

Examples

Want to learn more about Belgie's features? The examples below are small, runnable projects — each one focuses on a single capability.

• simple: Async Runtime with a TypeScript file on disk.
• inline-deps: Direct npm:, jsr:, and URL imports in a script.
• jsr-deps: JSR packages declared through an explicit Environment.
• environment: Sync and async Environment setup with path.
• commands: npm package binaries via Runtime and Command.
• pydantic-ai: Pydantic AI agent with the BelgieCapability capability and run_code tool.

For deeper integration guidance, optionally install the use-belgie skill with uvx library-skills install.