langchain-recourse 0.1.0

LangChain tools for RecourseOS - evaluate consequences before destructive actions

langchain-recourse

LangChain tools for RecourseOS - evaluate consequences before your AI agent executes destructive actions.

Installation

pip install langchain-recourse

Requires: Node.js 18+ (for npx recourse-cli)

Quick Start

from langchain_recourse import RecourseToolkit
from langchain_openai import ChatOpenAI
from langchain.agents import create_react_agent, AgentExecutor

# Get all RecourseOS tools
toolkit = RecourseToolkit()
tools = toolkit.get_tools()

# Create your agent with consequence checking
llm = ChatOpenAI(model="gpt-4")
agent = create_react_agent(llm, tools, prompt)
executor = AgentExecutor(agent=agent, tools=tools)

Tools

recourse_evaluate_terraform

Evaluate Terraform plans before terraform apply.

from langchain_recourse import RecourseEvaluateTerraform

tool = RecourseEvaluateTerraform()
result = tool.invoke({
    "plan_json": '{"resource_changes": [...]}'
})
# Returns: "**Risk Assessment: BLOCK** ..."

recourse_evaluate_shell

Evaluate shell commands before execution.

from langchain_recourse import RecourseEvaluateShell

tool = RecourseEvaluateShell()
result = tool.invoke({
    "command": "aws s3 rm s3://prod-data --recursive"
})
# Returns: "**Risk Assessment: BLOCK** ..."

recourse_evaluate_mcp

Evaluate MCP tool calls before invocation.

from langchain_recourse import RecourseEvaluateMCP

tool = RecourseEvaluateMCP()
result = tool.invoke({
    "server": "aws",
    "tool": "s3.delete_bucket",
    "arguments": {"bucket": "prod-data"}
})
# Returns: "**Risk Assessment: ESCALATE** ..."

Risk Levels

Level	Meaning	Agent Behavior
ALLOW	Safe to proceed	Execute normally
WARN	Recoverable but notable	Proceed with caution
ESCALATE	Needs human review	Ask user to confirm
BLOCK	Unrecoverable data loss	Do NOT proceed

Agent Integration Example

Here's a complete example of an agent that checks consequences before destructive actions:

from langchain_recourse import RecourseToolkit, RecourseEvaluateShell
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from langchain.agents import create_tool_calling_agent, AgentExecutor

# System prompt that enforces consequence checking
system_prompt = """You are a helpful DevOps assistant.

IMPORTANT: Before executing ANY destructive command (delete, remove, drop, etc.),
you MUST first use the recourse_evaluate_shell tool to check consequences.

If the risk assessment is:
- BLOCK: Refuse to proceed. Explain why to the user.
- ESCALATE: Ask the user to explicitly confirm before proceeding.
- WARN: Inform the user of the risk, then proceed if they agree.
- ALLOW: Proceed normally.

Never skip the consequence check for destructive operations."""

prompt = ChatPromptTemplate.from_messages([
    ("system", system_prompt),
    ("human", "{input}"),
    ("placeholder", "{agent_scratchpad}"),
])

# Setup
llm = ChatOpenAI(model="gpt-4")
tools = RecourseToolkit().get_tools()
agent = create_tool_calling_agent(llm, tools, prompt)
executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

# Run
result = executor.invoke({
    "input": "Delete the S3 bucket called prod-backups"
})

With Other Tools

Combine RecourseOS tools with your existing tools:

from langchain_recourse import RecourseToolkit
from langchain_community.tools import ShellTool

# Your tools + RecourseOS tools
my_tools = [ShellTool()]
recourse_tools = RecourseToolkit().get_tools()
all_tools = my_tools + recourse_tools

Configuration

The tools use npx recourse-cli@latest under the hood. Ensure:

1. Node.js 18+ is installed
2. npx is in PATH
3. Network access to npm registry (first run downloads the CLI)

License

MIT