#!/usr/bin/env python
"""
Basic usage example for Enkrypt AI Guardrails with LangChain.
This example shows how to use the EnkryptGuardrailsHandler with LangChain's
ChatOpenAI model.
Requirements:
pip install langchain langchain-openai
Environment:
OPENAI_API_KEY: Your OpenAI API key
ENKRYPT_API_KEY: Your Enkrypt API key (or configure in guardrails_config.json)
"""
import os
import sys
# Add parent directory to path for local imports
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from enkrypt_guardrails_handler import (
EnkryptGuardrailsHandler,
GuardrailsViolationError,
get_guardrails_metrics,
)
# Check for required API keys
if not os.environ.get("OPENAI_API_KEY"):
print("Warning: OPENAI_API_KEY not set. Set it to run this demo.")
print(" PowerShell: $env:OPENAI_API_KEY = 'your-key'")
print(" Bash: export OPENAI_API_KEY='your-key'")
def main():
"""Run basic usage demo."""
try:
from langchain_openai import ChatOpenAI
except ImportError:
print("Please install langchain-openai: pip install langchain-openai")
return
print("=" * 60)
print("Enkrypt AI Guardrails - Basic LangChain Usage Demo")
print("=" * 60)
# Create the guardrails handler
handler = EnkryptGuardrailsHandler(
raise_on_violation=True,
block_sensitive_tools=True,
)
# Create LLM with guardrails handler
llm = ChatOpenAI(
model="gpt-4o-mini",
temperature=0,
callbacks=[handler],
)
# Test 1: Safe prompt
print("\n--- Test 1: Safe Prompt ---")
try:
response = llm.invoke("What is Python programming language?")
print(f"Response: {response.content[:200]}...")
print("Result: PASSED (safe prompt allowed)")
except GuardrailsViolationError as e:
print(f"Unexpected block: {e}")
except Exception as e:
print(f"Error: {e}")
# Test 2: Another safe prompt
print("\n--- Test 2: Another Safe Prompt ---")
try:
response = llm.invoke("Explain machine learning in simple terms.")
print(f"Response: {response.content[:200]}...")
print("Result: PASSED (safe prompt allowed)")
except GuardrailsViolationError as e:
print(f"Unexpected block: {e}")
except Exception as e:
print(f"Error: {e}")
# Print metrics
print("\n--- Metrics ---")
metrics = get_guardrails_metrics()
for hook_name, hook_metrics in metrics.items():
if hook_metrics["total_calls"] > 0:
print(f" {hook_name}:")
print(f" Total calls: {hook_metrics['total_calls']}")
print(f" Blocked: {hook_metrics['blocked_calls']}")
print(f" Allowed: {hook_metrics['allowed_calls']}")
print(f" Avg latency: {hook_metrics['avg_latency_ms']:.2f}ms")
if __name__ == "__main__":
main()
