AgentWall Python Client SDK
Python client for the Vexa AgentWall AI Security Gateway & Firewall.
Routes AI agent tool calls and LLM egress through the out-of-process AgentWall proxy, enforcing default-deny policies, DLP secret redaction, prompt injection scanning, spend caps, and Human-in-the-Loop approvals without running governance logic in-process.
Installation
pip install vexaagentwall
Quick Start
Make sure agentwall is running locally (agentwall dev or via Docker / Kubernetes):
from agentwall import AgentWallClient, AgentWallDenied, AgentWallApprovalPending
# Auto-discovers local proxy at http://127.0.0.1:8080 or AGENTWALL_PROXY_URL env var
client = AgentWallClient()
# Method 1: Decorator for transparent governance
@client.governed
def read_project_file(path: str) -> str:
with open(path, "r") as f:
return f.read()
# Safe call
try:
content = read_project_file("/home/user/project/src/main.rs")
print(content)
except AgentWallDenied as e:
print(f"Blocked by policy: {e.rule_name} — {e.reason}")
except AgentWallApprovalPending as e:
print(f"Action requires human approval: {e.approval_url}")
# Method 2: Direct tool call routing
result = client.call_tool("read_file", {"path": "/home/user/project/README.md"})
print(result.data)
Async Support
import asyncio
from agentwall import AsyncAgentWallClient
async def main():
client = AsyncAgentWallClient()
@client.governed
async def async_fetch(url: str):
# Your tool logic
return "data"
res = await async_fetch("https://api.internal.corp/data")
print(res)
asyncio.run(main())
LangChain Integration
from langchain.tools import tool
from agentwall import AgentWallClient
client = AgentWallClient()
@tool
@client.governed
def query_customer_db(query: str) -> str:
"""Run read-only database query."""
return db.execute(query)
License
MIT License.
1 maintainer
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