agentlock-sdk 0.3.0

AgentLock Python SDK for AI agent integration

agentlock-sdk (Python)

Python SDK for integrating AI agents with AgentLock.

Installation

# The [nacl] extra installs the Ed25519 signing backend — without it,
# generate_keypair() and every signed request raise ImportError.
pip install "agentlock-sdk[nacl]"
# or with poetry:
poetry add agentlock-sdk -E nacl

Quick Start

from agentlock import AgentLockClient, generate_keypair

# Generate once
keypair = generate_keypair()
print("Public key (register in dashboard):", keypair.public_key)

# Create client
client = AgentLockClient(
    base_url="https://your-agentlock.vercel.app",
    agent_id="your-agent-id",
    private_key=keypair.private_key,  # or load from env
)

# Request an action
result = client.request_action(
    action_type="write",
    tool="http",
    payload={
        "url": "https://httpbin.org/post",
        "method": "POST",
        "body": {"message": "Hello from Python!"},
    },
)

print(result.decision)  # ALLOW | REQUIRE_APPROVAL | BLOCK

if result.status == "PENDING":
    final = client.await_result(result.request_id)
    print(final)

SDK Implementation

See src/agentlock/client.py for the full implementation. Uses pynacl for Ed25519 signing.

SSH sessions

with client.ssh.open(credential_id="cred-1") as session:
    print(session.run("uname -a").stdout)
    print(session.run("uptime").stdout)
# auto-closes

Re-attach to an existing session:

sessions = client.ssh.list()
ops = next((s for s in sessions if s.host == "ops-prod-01"), None)
if ops:
    print(ops.run("tail -n 50 /var/log/nginx/access.log").stdout)

Browser snapshot

snap = client.browser_snapshot(session_id)
# {"html": ..., "url": ..., "title": ..., "screenshot": ... (optional)}

HTTP requests

res = client.http_request(
    method="POST",
    url="https://api.example.com/items",
    body={"name": "x"},
    credential_id="cred-api",
)
# {"status": 201, "headers": {...}, "body": {...}, "duration_ms": 42}