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- Add EmailState model for Flow state management - Create EmailProcessingFlow class with event-based automation - Update tools and crews for Flow integration - Add comprehensive Flow tests - Implement error handling and state tracking - Add mock implementations for testing This implementation uses CrewAI Flow features to create an event-based email processing system that can analyze emails, research senders, and generate appropriate responses using specialized AI crews. Co-Authored-By: Joe Moura <joao@crewai.com>
61 lines
1.6 KiB
Python
61 lines
1.6 KiB
Python
"""
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Main workflow script for email processing system.
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Implements event-based automation for email analysis and response generation.
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"""
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from typing import Dict
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import logging
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from datetime import datetime
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from .email_flow import EmailProcessingFlow
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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def process_emails() -> Dict:
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"""
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Main workflow function.
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Implements event-based email processing using CrewAI Flow.
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Returns:
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Dict: Processing results including counts and any errors
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"""
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try:
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logger.info("Starting email processing workflow")
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# Initialize and start flow
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flow = EmailProcessingFlow()
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results = flow.kickoff()
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# Log processing results
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logger.info(
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f"Processed {results['processed_emails']} emails, "
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f"generated {results['responses_generated']} responses"
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)
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if results.get('errors', 0) > 0:
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logger.warning(f"Encountered {results['errors']} errors during processing")
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return {
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"timestamp": datetime.now().isoformat(),
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"status": "success",
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**results
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}
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except Exception as e:
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logger.error(f"Email processing failed: {str(e)}")
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return {
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"timestamp": datetime.now().isoformat(),
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"status": "error",
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"error": str(e)
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}
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if __name__ == "__main__":
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results = process_emails()
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print(f"\nProcessing Results:\n{'-' * 20}")
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for key, value in results.items():
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print(f"{key}: {value}")
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