[FEATURE] Support offline custom dependencies for Code Interpreter sessions

[tspython]

Is your feature request related to a problem? Please describe.

AgentCore Code Interpreter provides a fixed set of pre-installed libraries. The
SDK's install_packages() helper runs a normal pip install, which requires
access to PyPI or another package index.

Code Interpreter sessions running in an isolated VPC without NAT cannot use
this mechanism. Enabling public internet access solely to install dependencies
increases cost and weakens the sandbox's network isolation.

Code Interpreter supports mounting S3 Files and EFS through
filesystemConfigurations, but there is no first-class way to declare an
offline dependency bundle or initialization step. Applications must currently:

1. Mount or upload a wheelhouse.
2. Execute pip install --no-index manually after every session starts.
3. Configure sys.path and PYTHONPATH separately for executeCode and
   executeCommand.
4. Detect initialization failures themselves before allowing agent code to run.

This creates duplicated bootstrap logic and makes session readiness ambiguous.

Describe the solution you'd like

Add first-class support for application-defined, offline dependencies when
creating a Code Interpreter or starting a session.

One possible API shape would be:

client.start(
    identifier=interpreter_id,
    filesystem_configurations=[dependency_mount],
    dependency_configuration={
        "python": {
            "requirementsPath": "/mnt/dependencies/requirements.txt",
            "wheelhousePath": "/mnt/dependencies/wheels",
            "offline": True,
        }
    },
)