google--adk-python/contributing/samples/environment_and_skills/e2b_environment

E2B Environment Sample

Overview

A small data analysis agent that uses the E2BEnvironment with the EnvironmentToolset to download public datasets and analyze them inside an E2B remote sandbox.

Instead of running on the local machine, all commands and file operations execute in an isolated remote sandbox with internet access. Asked a question, the agent downloads a public dataset (a GCS-hosted world population / demographics dataset by default), installs pandas on demand, writes a short analysis script, runs it, and reports the result — all without touching the user's machine. This makes the sandbox a natural fit for running model-generated code safely and keeping the host clean.

The sandbox has a bounded time-to-live (timeout, in seconds) to cap credit usage. The TTL is reset on every operation, so an actively used workspace never expires mid-task; after genuine idle it expires and is transparently recreated on the next operation (note: workspace state such as installed packages and files is lost on recreation).

Prerequisites

1. Install the e2b extra:

   pip install google-adk[e2b]
   

2. Set your E2B API key (get one at https://e2b.dev):

   export E2B_API_KEY="your-api-key"
   

Sample Inputs

• Download the world demographics dataset and tell me which country has the largest population.

  The agent downloads the dataset, installs pandas, filters to country-level rows, and finds the maximum. Expected: China (CN), ≈ 1.44 billion, just ahead of India (IN) at ≈ 1.38 billion.

• For the United States, what is the urban vs rural population split?

  A follow-up to the previous turn. Because the sandbox persists across the session, the agent reuses the already-downloaded CSV and the installed pandas — it only writes and runs a new script. Expected for US: urban ≈ 270.7 million vs rural ≈ 57.6 million (out of ≈ 331 million total).

• Using https://storage.googleapis.com/cloud-samples-data/bigquery/us-states/us-states.csv, how many US states are listed?

  Demonstrates pointing the agent at your own dataset URL instead of the default.

Graph

graph TD
    User -->|question| Agent[data_analysis_agent]
    Agent -->|EnvironmentToolset| Sandbox[E2BEnvironment sandbox]
    Sandbox -->|download / install / run| Agent
    Agent -->|answer| User

How To

The agent is a standalone Agent (no workflow graph) wired to a single EnvironmentToolset whose environment is an E2BEnvironment:

from google.adk.integrations.e2b import E2BEnvironment
from google.adk.tools.environment import EnvironmentToolset

EnvironmentToolset(
    environment=E2BEnvironment(image="base", timeout=300),
)

• image selects the E2B template (defaults to the public base template).
• timeout bounds the sandbox lifetime in seconds to cap credit usage; it is reset on every operation.

The default GCS-hosted demographics CSV is a standard CSV with a header row. Each row is one location identified by location_key: country-level rows use a two-letter ISO code (e.g. US, CN), while subregions use keys containing an underscore (e.g. US_CA). The agent's instruction documents this schema — in particular, to filter out underscore keys when a question is about countries — so the generated analysis script parses and aggregates the file correctly.