Ever wished your agent could read PDFs, images, and Office documents as easily as plain text? Or combine the safety of a secure sandbox with the full power of Bash access? We built exactly that. Meet 𝘀𝗮𝗻𝗱𝗯𝗼𝘅𝗲𝗱-𝗹𝗶𝘁, a Rust CLI agent that combines: - LiteParse, our lightning-fast local parser for PDFs, images, Office files, and more - A secure sandbox powered by @microsandbox - Full filesystem mounting, so your agent can safely interact with local files inside the sandbox Mount your local workspace, give the agent shell access, and let it do its magic GitHub: http://github.com/run-llama/sandboxed-lit… Learn more about LiteParse: https://developers.llamaindex.ai/liteparse?utm_medium=socials&utm_source=twitter&utm_campaign=2026…–

run-llama/sandboxed-lit

Source: https://github.com/run-llama/sandboxed-lit

sandboxed-lit

A small Rust CLI that runs an LLM agent inside a microsandbox VM. The agent uses OpenAI’s GPT models via agent-sdk and has tools to list files, read files (parsing PDFs / images / Office docs through liteparse), and run bash commands, all confined to the sandbox.

How it works

• src/sandbox.rs — Creates (or reuses) a microsandbox named lit-sandbox from the ghcr.io/run-llama/liteparse:main image with 2 CPUs and 1 GB of RAM, working dir /app/, and a bind mount at /app/data. Exposes:
  • create_or_get_sandbox(volume) — boots / attaches to the sandbox.
  • list_files(sandbox, dir) — recursively lists files under /app/data.
  • read_file(sandbox, path) — reads a file; routes PDFs, images and Office docs through lit parse for structured extraction.
  • run_bash_command(sandbox, cmd, args) — runs an arbitrary command inside the sandbox and returns {stdout, stderr}.
• src/agent.rs — Wraps those functions as three agent-sdk tools (list_files, read_file, bash), registers them, builds an OpenAI-backed agent, streams events to the terminal with colored output, and runs until completion.
• src/main.rs — A clap CLI that parses the prompt and optional mount path and calls agent::run_agent.

Requirements

• Rust (edition 2024)
• A running microsandbox host (see the microsandbox docs)
• An OPENAI_API_KEY environment variable

Build

cargo build --release

Usage

sandboxed-lit --prompt "<your prompt>" [--volume <host-path>]

Options:

Examples

Run with the current directory mounted:

export OPENAI_API_KEY=sk-...
sandboxed-lit -p "Summarize every PDF in the working directory."

Mount a specific folder:

sandboxed-lit \
  -p "List the files, then read report.pdf and extract the key findings." \
  -v /Users/me/documents

Files in the mounted directory are visible to the agent at /app/data/....