langchain-aegis

Aegis governance integration for LangChain. Add policy enforcement to any LangChain tool with one function call.

Installation

pip install langchain-aegis

Quick Start

from langchain_aegis import govern_tools

# Wrap your existing tools — no other code changes needed
governed = govern_tools(tools, policy="policy.yaml")
agent = create_react_agent(model, governed)

What It Does

langchain-aegis evaluates every tool call against an Aegis YAML policy before execution. Blocked actions return a governance message instead of running.

Tool call → Aegis policy check → allowed? → execute
                                  blocked? → return "[BLOCKED by Aegis] ..."

Policy Example

# policy.yaml
version: "1"
defaults:
  risk_level: medium
  approval: auto
rules:
  - name: allow_reads
    match:
      type: "read_*"
    risk_level: low
    approval: auto

  - name: block_deletes
    match:
      type: "delete_*"
    risk_level: critical
    approval: block

API

govern_tool(tool, policy)

Wrap a single tool:

from langchain_aegis import govern_tool

governed_search = govern_tool(search_tool, policy="policy.yaml")
result = governed_search.invoke({"query": "AI governance"})

govern_tools(tools, policy)

Wrap multiple tools with the same policy:

from langchain_aegis import govern_tools

governed = govern_tools(
    [search_tool, calculator_tool, delete_tool],
    policy="policy.yaml",
)

Policy as object

from aegis import Policy

policy = Policy.from_yaml("policy.yaml")
governed = govern_tools(tools, policy=policy)

How It Works

• Tool name maps to Action.type in Aegis policy matching
• Tool input parameters map to Action.params
• Glob patterns in policy rules match tool names (delete_*, *)
• First matching rule wins — same as Aegis core
• Supports sync and async tool execution

Requirements

• Python 3.11+
• agent-aegis >= 0.1.3
• langchain-core >= 0.2

License

MIT — same as Aegis.