mirror of
https://github.com/awslabs/amazon-bedrock-agentcore-samples.git
synced 2025-09-08 20:50:46 +00:00
* feat: Add AWS Operations Agent with AgentCore Runtime - Complete rewrite of AWS Operations Agent using Amazon Bedrock AgentCore - Added comprehensive deployment scripts for DIY and SDK runtime modes - Implemented OAuth2/PKCE authentication with Okta integration - Added MCP (Model Context Protocol) tool support for AWS service operations - Sanitized all sensitive information (account IDs, domains, client IDs) with placeholders - Added support for 17 AWS services: EC2, S3, Lambda, CloudFormation, IAM, RDS, CloudWatch, Cost Explorer, ECS, EKS, SNS, SQS, DynamoDB, Route53, API Gateway, SES, Bedrock, SageMaker - Includes chatbot client, gateway management scripts, and comprehensive testing - Ready for public GitHub with security-cleared configuration files Security: All sensitive values replaced with <YOUR_AWS_ACCOUNT_ID>, <YOUR_OKTA_DOMAIN>, <YOUR_OKTA_CLIENT_ID> placeholders * Update AWS Operations Agent architecture diagram * feat: Enhance AWS Operations Agent with improved testing and deployment - Update README with new local container testing approach using run-*-local-container.sh scripts - Replace deprecated SAM-based MCP Lambda deployment with ZIP-based deployment - Add no-cache flag to Docker builds to ensure clean builds - Update deployment scripts to use consolidated configuration files - Add comprehensive cleanup scripts for all deployment components - Improve error handling and credential validation in deployment scripts - Add new MCP tool deployment using ZIP packaging instead of Docker containers - Update configuration management to use dynamic-config.yaml structure - Add local testing capabilities with containerized agents - Remove outdated test scripts and replace with interactive chat client approach * fix: Update IAM policy configurations - Update bac-permissions-policy.json with enhanced permissions - Update bac-trust-policy.json for improved trust relationships * fix: Update Docker configurations for agent runtimes - Update Dockerfile.diy with improved container configuration - Update Dockerfile.sdk with enhanced build settings * fix: Update OAuth iframe flow configuration - Update iframe-oauth-flow.html with improved OAuth handling * feat: Update AWS Operations Agent configuration and cleanup - Update IAM permissions policy with enhanced access controls - Update IAM trust policy with improved security conditions - Enhance OAuth iframe flow with better UX and error handling - Improve chatbot client with enhanced local testing capabilities - Remove cache files and duplicate code for cleaner repository * docs: Add architecture diagrams and update README - Add architecture-2.jpg and flow.jpg diagrams for better visualization - Update README.md with enhanced documentation and diagrams * Save current work before resolving merge conflicts * Keep AWS-operations-agent changes (local version takes precedence) * Fix: Remove merge conflict markers from AWS-operations-agent files - restore clean version * Fix deployment and cleanup script issues Major improvements and fixes: Configuration Management: - Fix role assignment in gateway creation (use bac-execution-role instead of Lambda role) - Add missing role_arn cleanup in MCP tool deletion script - Fix OAuth provider deletion script configuration clearing - Improve memory deletion script to preserve quote consistency - Add Lambda invoke permissions to bac-permissions-policy.json Script Improvements: - Reorganize deletion scripts: 11-delete-oauth-provider.sh, 12-delete-memory.sh, 13-cleanup-everything.sh - Fix interactive prompt handling in cleanup scripts (echo -e format) - Add yq support with sed fallbacks for better YAML manipulation - Remove obsolete 04-deploy-mcp-tool-lambda-zip.sh script Architecture Fixes: - Correct gateway role assignment to use runtime.role_arn (bac-execution-role) - Ensure proper role separation between gateway and Lambda execution - Fix configuration cleanup to clear all dynamic config fields consistently Documentation: - Update README with clear configuration instructions - Maintain security best practices with placeholder values - Add comprehensive deployment and cleanup guidance These changes address systematic issues with cleanup scripts, role assignments, and configuration management while maintaining security best practices. * Update README.md with comprehensive documentation Enhanced documentation includes: - Complete project structure with 75 files - Step-by-step deployment guide with all 13 scripts - Clear configuration instructions with security best practices - Dual agent architecture documentation (DIY + SDK) - Authentication flow and security implementation details - Troubleshooting guide and operational procedures - Local testing and container development guidance - Tool integration and MCP protocol documentation The README now provides complete guidance for deploying and operating the AWS Support Agent with Amazon Bedrock AgentCore system. --------- Co-authored-by: name <alias@amazon.com>
271 lines
12 KiB
Python
271 lines
12 KiB
Python
"""
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AWS Operations Agent Gateway Lambda Handler - Optimized Version
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Handles AWS resource inspection tools via Strands Agent integration
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Updated: 2025-08-02 - Added optimized system prompt with python_repl and shell tools
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"""
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import json
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import logging
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import os
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from datetime import datetime
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from typing import Dict, Any, Optional
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# Import Strands components at module level
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from strands import Agent, tool
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from strands.models import BedrockModel
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from strands_tools import use_aws, shell, calculator, think, current_time, stop, handoff_to_user
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STRANDS_AVAILABLE = True
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logging.info("Strands modules imported successfully with shell tool")
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# Configure logging
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logger = logging.getLogger()
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logger.setLevel(logging.INFO)
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# AWS Service Tool Configurations
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SERVICE_QUERIES = {
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# Core AWS Services
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'ec2_read_operations': "List and describe EC2 resources including instances, security groups, VPCs, subnets, and key pairs. Include instance states, types, and network configurations.",
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's3_read_operations': "List and describe S3 resources including buckets, bucket policies, lifecycle configurations, and access settings. Include bucket regions and creation dates.",
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'lambda_read_operations': "List and describe Lambda resources including functions, layers, aliases, and event source mappings. Include runtime, memory, timeout, and last modified information.",
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'cloudformation_read_operations': "List and describe CloudFormation resources including stacks, stack resources, stack events, and templates. Include stack status and creation times.",
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'iam_read_operations': "List and describe IAM resources including users, roles, policies, and groups. Include policy attachments and permissions (read-only operations only).",
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'rds_read_operations': "List and describe RDS and database resources including DB instances, clusters, snapshots, and parameter groups. Include engine types, versions, and status.",
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'cloudwatch_read_operations': "List and describe CloudWatch resources including metrics, alarms, log groups, and dashboards. Include alarm states and metric statistics.",
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'cost_explorer_read_operations': "Retrieve cost and billing information including cost breakdowns, usage reports, and budget information. Include cost trends and service-wise spending.",
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# Additional AWS Services
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'ecs_read_operations': "List and describe ECS resources including clusters, services, tasks, and task definitions. Include service status and task counts.",
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'eks_read_operations': "List and describe EKS resources including clusters, node groups, and add-ons. Include cluster status, versions, and configurations.",
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'sns_read_operations': "List and describe SNS resources including topics, subscriptions, and platform applications. Include topic ARNs and subscription counts.",
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'sqs_read_operations': "List and describe SQS resources including queues, queue attributes, and message statistics. Include queue types and visibility timeouts.",
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'dynamodb_read_operations': "List and describe DynamoDB resources including tables, indexes, and backups. Include table status, item counts, and throughput settings.",
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'route53_read_operations': "List and describe Route53 resources including hosted zones, record sets, and health checks. Include DNS configurations and routing policies.",
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'apigateway_read_operations': "List and describe API Gateway resources including REST APIs, resources, methods, and deployments. Include API stages and endpoint configurations.",
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'ses_read_operations': "List and describe SES resources including verified identities, configuration sets, and sending statistics. Include reputation metrics and quotas.",
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'bedrock_read_operations': "List and describe Bedrock resources including foundation models, model customization jobs, and inference profiles. Include model capabilities and availability.",
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'sagemaker_read_operations': "List and describe SageMaker resources including endpoints, models, training jobs, and notebook instances. Include status and configurations."
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}
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BASIC_TOOLS = ['hello_world', 'get_time']
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AWS_SERVICE_TOOLS = list(SERVICE_QUERIES.keys())
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ALL_TOOLS = BASIC_TOOLS + AWS_SERVICE_TOOLS
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def extract_tool_name(context, event: Dict[str, Any]) -> Optional[str]:
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"""Extract tool name from Gateway context or event."""
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# Try Gateway context first
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if hasattr(context, 'client_context') and context.client_context:
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if hasattr(context.client_context, 'custom') and context.client_context.custom:
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tool_name = context.client_context.custom.get('bedrockAgentCoreToolName')
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if tool_name and '___' in tool_name:
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# Remove namespace prefix (e.g., "aws-tools___hello_world" -> "hello_world")
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return tool_name.split('___', 1)[1]
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elif tool_name:
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return tool_name
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# Fallback to event-based extraction
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for field in ['tool_name', 'toolName', 'name', 'method', 'action', 'function']:
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if field in event:
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return event[field]
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# Infer from event structure
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if isinstance(event, dict):
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if 'name' in event and len(event) == 1:
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return 'hello_world' # Typical hello_world structure
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elif len(event) == 0:
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return 'get_time' # Empty args typically means get_time
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return None
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def handle_hello_world(event: Dict[str, Any]) -> Dict[str, Any]:
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"""Handle hello_world tool."""
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name = event.get('name', 'World')
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message = f"Hello, {name}! This message is from a Lambda function via AWS Operations Agent Gateway."
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return {
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'success': True,
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'result': message,
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'tool': 'hello_world',
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'timestamp': datetime.utcnow().isoformat() + 'Z'
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}
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def handle_get_time(event: Dict[str, Any]) -> Dict[str, Any]:
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"""Handle get_time tool."""
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current_time = datetime.utcnow().isoformat() + 'Z'
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return {
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'success': True,
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'result': f"Current UTC time: {current_time}",
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'tool': 'get_time',
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'timestamp': current_time
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}
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def handle_aws_service_tool(tool_name: str, event: Dict[str, Any]) -> Dict[str, Any]:
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"""Handle AWS service tools using Strands Agent."""
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# Check if Strands is available
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if not STRANDS_AVAILABLE:
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return {
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'success': False,
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'error': f"Strands modules not available for {tool_name}. Please check Lambda dependencies.",
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'tool': tool_name,
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'timestamp': datetime.utcnow().isoformat() + 'Z'
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}
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try:
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# Get the natural language query from the simplified schema
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user_query = event.get('query', '')
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if not user_query:
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return {
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'success': False,
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'error': f"Missing required 'query' parameter for {tool_name}",
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'tool': tool_name,
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'timestamp': datetime.utcnow().isoformat() + 'Z'
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}
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logger.info(f"Initializing Strands Agent for: {tool_name}")
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# Initialize Bedrock model
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bedrock_model = BedrockModel(
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region_name='us-east-1',
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model_id='us.anthropic.claude-3-5-haiku-20241022-v1:0', #'us.anthropic.claude-3-7-sonnet-20250219-v1:0',
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temperature=0.1
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)
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# Import loop control tools
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from strands_tools import stop, handoff_to_user
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# Create Strands Agent with loop control tools
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agent = Agent(
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model=bedrock_model,
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tools=[use_aws, stop, handoff_to_user, current_time],
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system_prompt="""
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You are an AWS assistant. IMPORTANT LOOP CONTROL RULES:
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1. Keep track of how many AWS operations you've performed
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2. If you've made more than 15 AWS tool calls, use the 'stop' tool immediately
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3. If you encounter repetitive operations, use 'handoff_to_user' to get guidance
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4. If you're stuck in a loop, call 'stop' with an explanation
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5. Always provide a summary before calling 'stop'
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Available tools for loop control:
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- stop: Gracefully terminate when done or when hitting limits
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- handoff_to_user: Get human guidance when uncertain
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- use_aws: Your main AWS operations tool
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CRITICAL: For any date-related queries, ALWAYS use the current_time tool first to get the current date before calculating date ranges.
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"""
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)
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# Build query
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# Get the natural language query from the simplified schema
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if not user_query:
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return {
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'success': False,
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'error': f"Missing required 'query' parameter for {tool_name}",
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'tool': tool_name,
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'timestamp': datetime.utcnow().isoformat() + 'Z'
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}
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# Build a simple, direct query (removed complex service context to prevent over-execution)
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#service_name = tool_name.replace('_read_operations', '').upper()
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#final_query = f"AWS {service_name}: {user_query}\n\nExecute this single operation directly and return results."
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#logger.info(f"Executing simplified query for {tool_name}: {user_query}")
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# Execute query
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#response = agent(final_query)
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response = agent(user_query)
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logger.info("##################################")
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print(str(response))
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logger.info("##################################")
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# Extract response text
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response_text = ""
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if hasattr(response, 'message') and 'content' in response.message:
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for content_block in response.message['content']:
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if content_block.get('type') == 'text' or 'text' in content_block:
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response_text += content_block.get('text', '')
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else:
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response_text = str(response)
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logger.info(f"Response length: {len(response_text)} characters")
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return response_text
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# return {
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# 'success': True,
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# 'result': response_text,
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# 'tool': tool_name,
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# 'service': tool_name.replace('_read_operations', '').replace('_', '-'),
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# 'user_query': user_query,
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# 'timestamp': datetime.utcnow().isoformat() + 'Z'
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# }
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except Exception as e:
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logger.error(f"AWS service tool error: {str(e)}")
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return {
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'success': False,
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'error': f"AWS Service Tool Error: {str(e)}",
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'tool': tool_name,
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'service': tool_name.replace('_read_operations', '').replace('_', '-'),
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'timestamp': datetime.utcnow().isoformat() + 'Z'
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}
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def lambda_handler(event, context):
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"""
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AWS Operations Agent Gateway Lambda Handler - Optimized Version
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Handles basic tools (hello_world, get_time) and AWS service tools
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via Strands Agent integration with comprehensive error handling.
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"""
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logger.info("AWS Operations Agent Gateway Lambda Handler - START")
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logger.info(f"Event: {json.dumps(event, default=str)}")
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try:
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# Extract tool name
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tool_name = extract_tool_name(context, event)
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logger.info(f"Tool: {tool_name}")
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if not tool_name:
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return {
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'success': False,
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'error': 'Unable to determine tool name from context or event',
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'available_tools': ALL_TOOLS,
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'timestamp': datetime.utcnow().isoformat() + 'Z'
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}
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# Route to appropriate handler
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if tool_name == 'hello_world':
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return handle_hello_world(event)
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elif tool_name == 'get_time':
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return handle_get_time(event)
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elif tool_name in AWS_SERVICE_TOOLS:
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return handle_aws_service_tool(tool_name, event)
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else:
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# Unknown tool
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return {
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'success': False,
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'error': f"Unknown tool: {tool_name}",
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'available_tools': ALL_TOOLS,
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'total_tools': len(ALL_TOOLS),
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'categories': {
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'basic': BASIC_TOOLS,
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'aws_services': AWS_SERVICE_TOOLS
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},
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'tool': tool_name,
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'timestamp': datetime.utcnow().isoformat() + 'Z'
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}
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except Exception as e:
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logger.error(f"Handler error: {str(e)}")
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return {
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'success': False,
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'error': f"Internal error: {str(e)}",
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'timestamp': datetime.utcnow().isoformat() + 'Z'
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}
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finally:
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logger.info("AWS Operations Agent Gateway Lambda Handler - END")
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