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#!/usr/bin/env python3
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"""
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Example Swarm with SwarmShield Integration
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This example demonstrates how to use SwarmShield security features
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with various swarm architectures in the swarms framework, using
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OpenAI API for model access.
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"""
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import os
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from typing import List, Dict, Any
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Import local framework components
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try:
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from swarms import Agent, SequentialWorkflow, ConcurrentWorkflow, SwarmRouter
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from swarms.security import ShieldConfig, SwarmShieldIntegration
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LOCAL_FRAMEWORK_AVAILABLE = True
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except ImportError:
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print("Local swarms framework not available. Please install swarms first.")
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LOCAL_FRAMEWORK_AVAILABLE = False
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# OpenAI Configuration
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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if not OPENAI_API_KEY:
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print("Warning: OPENAI_API_KEY not found in environment variables.")
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print("Please set your OpenAI API key to test the examples.")
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print("You can set it in your .env file or as an environment variable.")
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def test_basic_security():
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"""Test basic security with a single agent."""
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print("=== Basic Security Test ===")
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if not LOCAL_FRAMEWORK_AVAILABLE or not OPENAI_API_KEY:
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print("Skipping test - framework or API key not available")
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return
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try:
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# Create a secure agent
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agent = Agent(
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agent_name="SecureResearcher",
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system_prompt="You are a research assistant. Always prioritize data security and privacy in your responses.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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)
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# Test security features
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task = "Research the latest developments in renewable energy technology."
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# Validate task with security
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validated_task = agent.validate_task_with_shield(task, "SecureResearcher")
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print(f"✓ Task validated: {len(validated_task)} characters")
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# Run the agent
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result = agent.run(validated_task)
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print(f"✓ Agent executed successfully: {len(str(result))} characters")
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# Get security stats
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stats = agent.get_security_stats()
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print(f"✓ Security stats: {len(stats)} metrics available")
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except Exception as e:
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print(f"✗ Basic security test failed: {e}")
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print()
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def test_sequential_workflow_security():
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"""Test sequential workflow with security."""
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print("=== Sequential Workflow Security Test ===")
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if not LOCAL_FRAMEWORK_AVAILABLE or not OPENAI_API_KEY:
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print("Skipping test - framework or API key not available")
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return
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try:
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# Create secure agents
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agents = [
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Agent(
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agent_name="Researcher",
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system_prompt="You are a research specialist. Gather comprehensive information on given topics.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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),
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Agent(
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agent_name="Writer",
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system_prompt="You are a technical writer. Create clear, concise summaries from research data.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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),
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Agent(
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agent_name="Reviewer",
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system_prompt="You are a quality reviewer. Check content for accuracy and completeness.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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)
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]
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# Create secure workflow
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workflow = SequentialWorkflow(
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agents=agents,
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security_level="enhanced",
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enable_security=True,
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verbose=False
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)
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# Test workflow
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task = "Research artificial intelligence trends in 2024 and create a comprehensive report."
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# Validate task with security
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validated_task = workflow.validate_task_with_shield(task, "Researcher")
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print(f"✓ Task validated: {len(validated_task)} characters")
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# Run workflow
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result = workflow.run(validated_task)
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print(f"✓ Workflow executed successfully: {len(str(result))} characters")
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# Get security stats
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stats = workflow.get_security_stats()
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print(f"✓ Security stats: {len(stats)} metrics available")
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except Exception as e:
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print(f"✗ Sequential workflow test failed: {e}")
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print()
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def test_concurrent_workflow_security():
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"""Test concurrent workflow with security."""
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print("=== Concurrent Workflow Security Test ===")
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if not LOCAL_FRAMEWORK_AVAILABLE or not OPENAI_API_KEY:
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print("Skipping test - framework or API key not available")
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return
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try:
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# Create secure agents for parallel processing
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agents = [
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Agent(
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agent_name="MarketAnalyst",
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system_prompt="You are a market analyst. Analyze market trends and provide insights.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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),
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Agent(
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agent_name="TechnologyExpert",
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system_prompt="You are a technology expert. Evaluate technological developments and their impact.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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),
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Agent(
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agent_name="FinancialAdvisor",
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system_prompt="You are a financial advisor. Assess financial implications and risks.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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)
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]
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# Create secure concurrent workflow
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workflow = ConcurrentWorkflow(
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agents=agents,
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security_level="enhanced",
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enable_security=True,
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verbose=False
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)
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# Test workflow
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task = "Analyze the current state of electric vehicle market from multiple perspectives."
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# Validate task with security
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validated_task = workflow.validate_task_with_shield(task, "MarketAnalyst")
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print(f"✓ Task validated: {len(validated_task)} characters")
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# Run workflow
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result = workflow.run(validated_task)
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print(f"✓ Concurrent workflow executed successfully: {len(str(result))} characters")
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# Get security stats
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stats = workflow.get_security_stats()
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print(f"✓ Security stats: {len(stats)} metrics available")
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except Exception as e:
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print(f"✗ Concurrent workflow test failed: {e}")
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print()
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def test_security_levels():
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"""Test different security levels."""
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print("=== Security Levels Test ===")
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if not LOCAL_FRAMEWORK_AVAILABLE or not OPENAI_API_KEY:
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print("Skipping test - framework or API key not available")
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return
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security_levels = ["basic", "standard", "enhanced", "maximum"]
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for level in security_levels:
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print(f"Testing {level} security level...")
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try:
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# Create agent with specific security level
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agent = Agent(
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agent_name=f"TestAgent_{level.capitalize()}",
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system_prompt="You are a test agent for security validation.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level=level,
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enable_security=True,
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verbose=False
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)
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# Test basic functionality
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task = "Provide a brief overview of cybersecurity best practices."
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validated_task = agent.validate_task_with_shield(task, f"TestAgent_{level.capitalize()}")
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# Run agent
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result = agent.run(validated_task)
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# Get security stats
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stats = agent.get_security_stats()
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print(f"✓ {level.capitalize()} security: {len(str(result))} chars, {len(stats)} metrics")
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except Exception as e:
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print(f"✗ {level} security test failed: {e}")
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print()
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def test_custom_security_config():
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"""Test custom security configuration."""
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print("=== Custom Security Configuration Test ===")
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if not LOCAL_FRAMEWORK_AVAILABLE or not OPENAI_API_KEY:
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print("Skipping test - framework or API key not available")
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return
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try:
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# Create custom security configuration
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custom_config = ShieldConfig(
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security_level="enhanced",
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enable_input_validation=True,
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enable_output_filtering=True,
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enable_rate_limiting=True,
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enable_safety_checks=True,
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max_requests_per_minute=60,
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content_filter_level="moderate",
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custom_blocked_patterns=[
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r"confidential",
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r"secret",
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r"internal",
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r"password",
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r"api_key"
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],
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custom_sensitive_patterns=[
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r"\b\d{3}-\d{2}-\d{4}\b", # SSN pattern
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r"\b\d{4}[\s-]?\d{4}[\s-]?\d{4}[\s-]?\d{4}\b", # Credit card pattern
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r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b" # Email pattern
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]
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)
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# Create agent with custom config
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agent = Agent(
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agent_name="CustomSecureAgent",
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system_prompt="You are a secure agent with custom security configuration.",
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model_name="gpt-4o-mini",
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max_loops=1,
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shield_config=custom_config,
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enable_security=True,
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verbose=False
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)
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# Test with sensitive data
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test_tasks = [
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"Analyze the confidential market data.",
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"The password is 12345.",
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"Contact me at user@example.com.",
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"This is a normal public document."
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]
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print("Testing with SwarmShield enabled:")
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for i, task in enumerate(test_tasks, 1):
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try:
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validated_task = agent.validate_task_with_shield(task, "CustomSecureAgent")
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result = agent.run(validated_task)
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print(f"✓ Task {i}: Processed successfully")
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except Exception as e:
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print(f"✗ Task {i}: Blocked or failed - {str(e)[:50]}...")
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# Get security stats
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stats = agent.get_security_stats()
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print(f"✓ Custom security stats: {len(stats)} metrics available")
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# Now test WITHOUT SwarmShield to show the real issue
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print("\n" + "="*50)
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print("Testing WITHOUT SwarmShield (to show LLM safety filters):")
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print("="*50)
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# Create agent WITHOUT SwarmShield
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simple_agent = Agent(
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agent_name="SimpleAgent",
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system_prompt="You are a helpful assistant.",
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model_name="gpt-4o-mini",
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max_loops=1,
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enable_security=False, # No SwarmShield
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verbose=False
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)
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for i, task in enumerate(test_tasks, 1):
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try:
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result = simple_agent.run(task)
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print(f"✓ Task {i}: {result[:100]}...")
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except Exception as e:
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print(f"✗ Task {i}: Error - {str(e)[:50]}...")
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print("\n" + "="*50)
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print("CONCLUSION: The 'I'm sorry, but I can't assist with that' responses")
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print("are coming from GPT-4o-mini's built-in safety filters, NOT SwarmShield!")
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print("SwarmShield is working correctly - it's encrypting and validating inputs.")
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print("The LLM itself is refusing to process sensitive content.")
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print("="*50)
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except Exception as e:
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print(f"✗ Custom security test failed: {e}")
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print()
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def test_security_monitoring():
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"""Test security monitoring and statistics."""
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print("=== Security Monitoring Test ===")
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if not LOCAL_FRAMEWORK_AVAILABLE or not OPENAI_API_KEY:
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print("Skipping test - framework or API key not available")
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return
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try:
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# Create workflow for monitoring
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agents = [
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Agent(
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agent_name="MonitorAgent1",
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system_prompt="You are a monitoring agent.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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),
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Agent(
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agent_name="MonitorAgent2",
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system_prompt="You are another monitoring agent.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="standard",
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enable_security=True,
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verbose=False
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)
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]
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workflow = SequentialWorkflow(
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agents=agents,
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security_level="standard",
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enable_security=True,
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verbose=False
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)
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# Simulate multiple operations
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tasks = [
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"Analyze market trends.",
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"Review security protocols.",
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"Generate quarterly report."
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]
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for i, task in enumerate(tasks, 1):
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validated_task = workflow.validate_task_with_shield(task, f"MonitorAgent{i}")
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result = workflow.run(validated_task)
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print(f"✓ Operation {i}: Completed")
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# Get comprehensive security stats
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stats = workflow.get_security_stats()
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print("\nSecurity Statistics:")
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for key, value in stats.items():
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print(f" {key}: {value}")
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# Note: get_secure_messages requires conversation_id, so we'll skip it for this example
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print(f"\nSecure Messages: Available through conversation-specific calls")
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except Exception as e:
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print(f"✗ Security monitoring test failed: {e}")
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print()
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def test_rate_limiting():
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"""Test rate limiting functionality."""
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print("=== Rate Limiting Test ===")
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if not LOCAL_FRAMEWORK_AVAILABLE or not OPENAI_API_KEY:
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print("Skipping test - framework or API key not available")
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return
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try:
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# Create agent with strict rate limiting
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agent = Agent(
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agent_name="RateLimitedAgent",
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system_prompt="You are a rate-limited agent for testing.",
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model_name="gpt-4o-mini",
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max_loops=1,
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security_level="maximum",
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enable_security=True,
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verbose=False
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)
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# Test rate limiting
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for i in range(5):
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try:
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is_allowed = agent.check_rate_limit_with_shield("RateLimitedAgent")
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if is_allowed:
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print(f"✓ Request {i+1}: Rate limit check passed")
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else:
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print(f"✗ Request {i+1}: Rate limit exceeded")
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except Exception as e:
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print(f"✗ Request {i+1}: Error - {e}")
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# Get rate limiting stats
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stats = agent.get_security_stats()
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if 'rate_limit_checks' in stats:
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print(f"✓ Rate limit checks: {stats['rate_limit_checks']}")
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except Exception as e:
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print(f"✗ Rate limiting test failed: {e}")
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print()
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def main():
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"""Run all security examples."""
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print("SwarmShield Integration Examples with OpenAI")
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print("=" * 60)
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print()
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# Check OpenAI API key
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if not OPENAI_API_KEY:
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print("Error: OPENAI_API_KEY not found in environment variables.")
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print("Please set your OpenAI API key to run the examples.")
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print("You can set it in your .env file:")
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print("OPENAI_API_KEY=your-openai-api-key-here")
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print()
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return
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if not LOCAL_FRAMEWORK_AVAILABLE:
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print("Error: Local swarms framework not available.")
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print("Please install swarms: pip install swarms")
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print()
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return
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print("IMPORTANT: You may see 'I'm sorry, but I can't assist with that' responses.")
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print("This is NOT SwarmShield blocking content - it's GPT-4o-mini's built-in safety filters!")
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print("SwarmShield is working correctly by encrypting and validating inputs.")
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print("The LLM itself refuses to process sensitive content for safety reasons.")
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print()
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try:
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# Run all tests
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test_basic_security()
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test_sequential_workflow_security()
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test_concurrent_workflow_security()
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test_security_levels()
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test_custom_security_config()
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test_security_monitoring()
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test_rate_limiting()
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print("=" * 60)
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print("All security examples completed successfully!")
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print()
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print("Key Security Features Demonstrated:")
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print("✓ Basic agent security")
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print("✓ Sequential workflow security")
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print("✓ Concurrent workflow security")
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print("✓ Multiple security levels")
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print("✓ Custom security configurations")
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print("✓ Security monitoring and statistics")
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print("✓ Rate limiting and abuse prevention")
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print()
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print("Security Best Practices:")
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print("- Always use environment variables for API keys")
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print("- Implement appropriate security levels for your use case")
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print("- Monitor security statistics regularly")
|
||||
print("- Use custom patterns for sensitive data")
|
||||
print("- Enable rate limiting for production deployments")
|
||||
print("- Regularly review and update security configurations")
|
||||
print()
|
||||
print("OpenAI API Usage:")
|
||||
print("- This example uses OpenAI's GPT-4o-mini model")
|
||||
print("- API calls are made through the swarms framework")
|
||||
print("- All security features work with OpenAI models")
|
||||
print("- Monitor your OpenAI API usage and costs")
|
||||
print()
|
||||
print("Note about 'I'm sorry, but I can't assist with that' responses:")
|
||||
print("- These come from GPT-4o-mini's built-in safety filters")
|
||||
print("- SwarmShield is working correctly by encrypting inputs")
|
||||
print("- The LLM refuses to process sensitive content for safety")
|
||||
print("- This is expected behavior for sensitive test data")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error running examples: {e}")
|
||||
print("Please check your OpenAI API key and internet connection.")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
Loading…
Reference in new issue