agentfense 0.2.1

Python SDK for AgentFense - A sandbox infrastructure service for AI Agents with fine-grained file permission control

AgentFense SDK for Python

Python client library for the AgentFense service - a sandbox infrastructure for AI Agents with fine-grained file permission control.

Installation

pip install agentfense

Or install from source:

cd sdk/python
pip install -e .

Quick Start (High-Level API)

The easiest way to use the SDK is with the high-level Sandbox class:

from agentfense import Sandbox

# One-liner to create a sandbox from a local directory
with Sandbox.from_local("./my-project") as sandbox:
    result = sandbox.run("python main.py")
    print(result.stdout)

This automatically:

1. Creates a codebase
2. Uploads all files from the directory
3. Creates a sandbox with the "agent-safe" preset
4. Starts the sandbox
5. Cleans up everything when done

Using Docker Runtime with Resource Limits

from agentfense import Sandbox, RuntimeType, ResourceLimits

with Sandbox.from_local(
    "./my-project",
    preset="agent-safe",
    runtime=RuntimeType.DOCKER,
    image="python:3.11-slim",
    resources=ResourceLimits(
        memory_bytes=512 * 1024 * 1024,  # 512 MB
        pids_limit=100,
    ),
) as sandbox:
    # Use a session for stateful commands
    with sandbox.session() as session:
        session.exec("cd /workspace")
        session.exec("pip install -r requirements.txt")
        result = session.exec("pytest")
        print(result.stdout)

Permission Presets

The SDK includes several built-in permission presets:

Preset	Description
agent-safe	Read all files, write to /output and /tmp, hide secrets (.env, *.key, etc.)
read-only	Read all files, no write access
full-access	Full read/write access to all files
development	Full access except secrets
view-only	Can see file names but not read content

from agentfense import list_presets, get_preset, extend_preset

# List all available presets
print(list_presets())  # ['agent-safe', 'development', 'full-access', 'read-only', 'view-only']

# Extend a preset with custom rules
rules = extend_preset(
    "agent-safe",
    additions=[{"pattern": "/custom/**", "permission": "write"}],
)

Error Handling

The SDK provides semantic exception classes:

from agentfense import Sandbox, SandboxError, CommandTimeoutError, CommandExecutionError

try:
    with Sandbox.from_local("./my-project") as sandbox:
        result = sandbox.run("python main.py", timeout=30, raise_on_error=True)
except CommandTimeoutError as e:
    print(f"Command timed out: {e}")
except CommandExecutionError as e:
    print(f"Command failed with exit code {e.exit_code}: {e.stderr}")
except SandboxError as e:
    print(f"Sandbox error: {e}")

Low-Level API

For fine-grained control, use the SandboxClient directly:

from agentfense import SandboxClient, RuntimeType, ResourceLimits

# Connect to the sandbox server
client = SandboxClient(endpoint="localhost:9000")

# Create a codebase (file storage)
codebase = client.create_codebase(name="my-project", owner_id="user_123")

# Upload a file
client.upload_file(codebase.id, "hello.py", b'print("Hello, World!")')

# Create a sandbox with permissions and Docker runtime
sandbox = client.create_sandbox(
    codebase_id=codebase.id,
    permissions=[
        {"pattern": "**/*.py", "permission": "read"},
        {"pattern": "/docs/**", "permission": "write"},
    ],
    runtime=RuntimeType.DOCKER,
    image="python:3.11-slim",
    resources=ResourceLimits(memory_bytes=256 * 1024 * 1024),
)

# Start the sandbox
client.start_sandbox(sandbox.id)

# Execute a command
result = client.exec(sandbox.id, command="python hello.py")
print(result.stdout)  # Output: Hello, World!

# Clean up
client.destroy_sandbox(sandbox.id)
client.delete_codebase(codebase.id)

Features

Permission Levels

The SDK supports four permission levels:

Level	Description
none	Completely invisible, not shown in ls
view	Visible in ls, but cannot read content
read	Can read file content
write	Can modify file

Permission Patterns

You can use glob patterns, directory paths, or file paths:

from agentfense import PermissionRule, Permission, PatternType

permissions = [
    # Glob pattern - matches all .py files
    PermissionRule(pattern="**/*.py", permission=Permission.READ),
    
    # Directory - applies to entire directory
    PermissionRule(pattern="/docs/", permission=Permission.WRITE, type=PatternType.DIRECTORY),
    
    # Specific file
    PermissionRule(pattern="/config.yaml", permission=Permission.VIEW, type=PatternType.FILE),
]

sandbox = client.create_sandbox(codebase_id=codebase.id, permissions=permissions)

Stateful Sessions

Sessions maintain a persistent shell process that preserves working directory and environment variables:

with client.session(sandbox.id) as session:
    session.exec("cd /workspace/src")     # Change directory
    session.exec("export DEBUG=1")         # Set environment variable
    session.exec("source venv/bin/activate")  # Activate virtualenv
    result = session.exec("python main.py")   # All above state is preserved

Command Execution

Execute commands with optional stdin, environment variables, and timeout:

from datetime import timedelta

result = client.exec(
    sandbox_id=sandbox.id,
    command="python script.py",
    stdin="input data",
    env={"DEBUG": "1"},
    workdir="/workspace/src",
    timeout=timedelta(seconds=30),
)

print(f"Exit code: {result.exit_code}")
print(f"stdout: {result.stdout}")
print(f"stderr: {result.stderr}")
print(f"Duration: {result.duration}")

Streaming Output

For long-running commands, use streaming:

for chunk in client.exec_stream(sandbox.id, command="long-running-task"):
    print(chunk.decode(), end="")

File Operations

# List files
files = client.list_files(codebase.id, path="/src", recursive=True)
for f in files:
    print(f"{f.path} - {f.size} bytes")

# Download a file
content = client.download_file(codebase.id, "config.yaml")
print(content.decode())

# Upload a file
result = client.upload_file(codebase.id, "new_file.txt", b"file content")
print(f"Uploaded {result.size} bytes, checksum: {result.checksum}")

Context Manager

Both the high-level Sandbox and low-level SandboxClient support context managers:

# High-level (recommended)
with Sandbox.from_local("./project") as sandbox:
    sandbox.run("make test")
# Automatically cleans up sandbox and codebase

# Low-level
with SandboxClient(endpoint="localhost:9000") as client:
    sandbox = client.create_sandbox(codebase_id="cb_123")
    # ... use the sandbox ...
# Connection is automatically closed

API Reference

High-Level API

Sandbox Class

• Sandbox.from_local(path, preset, permissions, runtime, image, resources, ...) - Create sandbox from local directory
• Sandbox.from_codebase(codebase_id, preset, ...) - Create sandbox from existing codebase
• Sandbox.connect(sandbox_id) - Connect to existing sandbox
• sandbox.run(command, timeout, env, workdir, raise_on_error) - Execute command (simplified)
• sandbox.exec(command, stdin, env, workdir, timeout) - Execute command (full API)
• sandbox.session(shell, env) - Create stateful session
• sandbox.read_file(path) - Read file as string
• sandbox.write_file(path, content) - Write file
• sandbox.list_files(path, recursive) - List files
• sandbox.start() / sandbox.stop() - Lifecycle control
• sandbox.destroy(delete_codebase) - Clean up

Presets

• get_preset(name) - Get preset as PermissionRule list
• get_preset_dicts(name) - Get preset as dict list
• extend_preset(base, additions, overrides) - Extend preset
• list_presets() - List available presets
• register_preset(name, rules) - Register custom preset

Low-Level API

SandboxClient

• create_sandbox(codebase_id, permissions, runtime, image, resources, labels, expires_in) - Create sandbox
• get_sandbox(sandbox_id) - Get sandbox info
• list_sandboxes(codebase_id) - List sandboxes
• start_sandbox(sandbox_id) - Start sandbox
• stop_sandbox(sandbox_id) - Stop sandbox
• destroy_sandbox(sandbox_id) - Destroy sandbox
• exec(sandbox_id, command, stdin, env, workdir, timeout) - Execute command
• exec_stream(sandbox_id, command, ...) - Execute with streaming
• create_session(sandbox_id, shell, env) - Create session
• session_exec(session_id, command, timeout) - Execute in session
• create_codebase(name, owner_id) - Create codebase
• get_codebase(codebase_id) - Get codebase info
• list_codebases(owner_id) - List codebases
• delete_codebase(codebase_id) - Delete codebase
• upload_file(codebase_id, file_path, content) - Upload file
• download_file(codebase_id, file_path) - Download file
• list_files(codebase_id, path, recursive) - List files

Types

• RuntimeType - BWRAP, DOCKER
• ResourceLimits - memory_bytes, cpu_quota, cpu_shares, pids_limit
• Permission - NONE, VIEW, READ, WRITE
• PatternType - GLOB, DIRECTORY, FILE
• SandboxStatus - PENDING, RUNNING, STOPPED, ERROR
• SessionStatus - UNKNOWN, ACTIVE, CLOSED

Exceptions

• SandboxError - Base exception
• SandboxNotFoundError - Sandbox not found
• SandboxNotRunningError - Sandbox not running
• CodebaseError - Codebase operation error
• CodebaseNotFoundError - Codebase not found
• CommandTimeoutError - Command timed out
• CommandExecutionError - Command failed (non-zero exit)
• PermissionDeniedError - Permission denied
• SessionError - Session operation error
• ConnectionError - Connection to service failed

Development

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black agentfense tests
ruff check --fix agentfense tests

# Type check
mypy agentfense

License

MIT