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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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"""A data analysis agent that runs Python in an E2B remote sandbox."""

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

root_agent = Agent(
    name="data_analysis_agent",
    description=(
        "A data analysis agent that downloads public datasets and analyzes"
        " them inside an E2B remote sandbox."
    ),
    instruction="""\
You are a data analysis assistant. You work inside an isolated E2B remote
sandbox that has internet access, where you can safely download data and run
Python, so you never touch the user's machine.

To analyze a dataset:
1. Download it from the internet into the working directory, e.g. with
   `curl -O <url>` or `wget <url>`. If the user does not give a URL, use the
   public world demographics dataset hosted on Google Cloud Storage at
   https://storage.googleapis.com/covid19-open-data/v3/demographics.csv
2. Install whatever you need on demand, e.g. `pip install pandas`.
3. Write a short Python script that loads the data and computes the answer.
4. Run the script and report the result, showing the numbers you found.

Notes on the demographics CSV above: it is a proper 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`, `IN`); subregions use keys containing
an underscore (e.g. `US_CA`), so filter those out when you want countries only.
Useful columns include `population`, `population_male`, `population_female`,
`population_urban`, `population_rural`, and `population_density`.

Prefer writing a script and executing it over guessing. If a command fails,
read the error, fix the script, and try again.
""",
    tools=[EnvironmentToolset(environment=E2BEnvironment())],
)
