llama-recourse 0.1.0

LlamaIndex tools for RecourseOS - evaluate consequences before destructive actions

llama-recourse

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

Installation

pip install llama-recourse

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

Quick Start

from llama_recourse import get_recourse_tools
from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI

# Get RecourseOS tools
tools = get_recourse_tools()

# Create agent with consequence checking
llm = OpenAI(model="gpt-4")
agent = ReActAgent.from_tools(
    tools,
    llm=llm,
    verbose=True,
    system_prompt="""Before any destructive action, use recourse_evaluate_* tools.
    If risk is BLOCK, refuse to proceed. If ESCALATE, ask user to confirm."""
)

response = agent.chat("Delete the S3 bucket prod-backups")

Tools

recourse_evaluate_terraform

Evaluate Terraform plans before terraform apply.

from llama_recourse import recourse_evaluate_terraform

result = recourse_evaluate_terraform(
    plan_json='{"resource_changes": [...]}',
    state_json=None  # optional
)
print(result)
# **Risk Assessment: BLOCK**
# ...

recourse_evaluate_shell

Evaluate shell commands before execution.

from llama_recourse import recourse_evaluate_shell

result = recourse_evaluate_shell("aws s3 rm s3://prod-data --recursive")
print(result)
# **Risk Assessment: BLOCK**
# ...

recourse_evaluate_mcp

Evaluate MCP tool calls before invocation.

from llama_recourse import recourse_evaluate_mcp

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

Full Agent Example

from llama_recourse import get_recourse_tools
from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI
from llama_index.core.tools import FunctionTool

# Your existing tools
def execute_shell(command: str) -> str:
    """Execute a shell command."""
    import subprocess
    result = subprocess.run(command, shell=True, capture_output=True, text=True)
    return result.stdout or result.stderr

shell_tool = FunctionTool.from_defaults(
    fn=execute_shell,
    name="execute_shell",
    description="Execute a shell command"
)

# Combine with RecourseOS tools
all_tools = [shell_tool] + get_recourse_tools()

# Create safety-aware agent
agent = ReActAgent.from_tools(
    all_tools,
    llm=OpenAI(model="gpt-4"),
    verbose=True,
    system_prompt="""You are a DevOps assistant.

CRITICAL: Before using execute_shell with ANY destructive command,
you MUST first use recourse_evaluate_shell to check consequences.

Based on the risk assessment:
- BLOCK: Refuse to proceed. Explain the danger.
- ESCALATE: Ask for explicit user confirmation.
- WARN: Inform user of risks, proceed if they agree.
- ALLOW: Proceed normally."""
)

# The agent will now check consequences before destructive actions
response = agent.chat("Remove all files from /tmp/old-backups")
print(response)

With Query Engine Tools

from llama_recourse import get_recourse_tools
from llama_index.core.agent import ReActAgent
from llama_index.core.tools import QueryEngineTool

# Your query engine
query_tool = QueryEngineTool.from_defaults(
    query_engine=index.as_query_engine(),
    name="docs_search",
    description="Search documentation"
)

# Add RecourseOS for safety
tools = [query_tool] + get_recourse_tools()
agent = ReActAgent.from_tools(tools, llm=llm)

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

Requirements

• Python 3.9+
• Node.js 18+ (for npx recourse-cli)
• llama-index-core>=0.10.0

License

MIT