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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>
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
from crewai import Agent, Task, Crew, Process
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from typing import List
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import json
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from pydantic import BaseModel
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import os
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# Define output models
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class EmailAnalysis(BaseModel):
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needs_response: bool
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priority: str
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context: str
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# Sample email data for testing
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SAMPLE_EMAIL = {
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"subject": "Meeting Follow-up",
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"body": "Thanks for the great discussion yesterday. Looking forward to next steps.",
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"sender": "john@example.com"
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}
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# Test Agent Creation
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researcher = Agent(
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role="Email Researcher",
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goal="Analyze email content and gather relevant context",
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backstory="Expert at analyzing communication patterns and gathering contextual information",
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verbose=True,
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allow_delegation=True
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)
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# Test Task Creation
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analysis_task = Task(
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description=f"Analyze this email content and determine if it requires a response: {json.dumps(SAMPLE_EMAIL)}",
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agent=researcher,
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expected_output="Detailed analysis of email content and response requirement",
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output_json=EmailAnalysis
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)
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# Test Crew Creation with Sequential Process
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crew = Crew(
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agents=[researcher],
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tasks=[analysis_task],
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process=Process.sequential,
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verbose=True
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)
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# Test execution with error handling
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if __name__ == "__main__":
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try:
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# Ensure we have an API key
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if not os.getenv("OPENAI_API_KEY"):
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print("Please set OPENAI_API_KEY environment variable")
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exit(1)
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result = crew.kickoff()
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print("Execution Results:", result)
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# Access structured output
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if hasattr(result, "output") and result.output:
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analysis = EmailAnalysis.parse_raw(result.output)
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print("\nStructured Analysis:")
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print(f"Needs Response: {analysis.needs_response}")
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print(f"Priority: {analysis.priority}")
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print(f"Context: {analysis.context}")
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except Exception as e:
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print(f"Error during execution: {str(e)}")
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