bolade
75a0a3fde7
- Added `get_latest_email_date()` function in `database.py` to retrieve the most recent email date for a given account and folder. - Enhanced `fetch_folder_emails()` in `zoho_client.py` to intelligently determine the start date for fetching emails based on the latest email date in the database. - Introduced `analyze_and_update_threads_async()` for asynchronous analysis of email threads, allowing concurrent processing. - Created a synchronous wrapper `analyze_and_update_threads()` for easier integration. - Updated `fetch_emails()` to support database session and account email parameters. - Added comprehensive documentation in `AI_ANALYSIS_GUIDE.md` detailing the new AI analysis functionality. - Implemented tests for the new features, including `test_fetch_with_db.py`, `test_ai_analysis.py`, and `test_single_analysis.py`. - Added error handling and logging improvements throughout the codebase.
100 lines
2.8 KiB
Python
100 lines
2.8 KiB
Python
#!/usr/bin/env python3
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"""
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Test script to demonstrate the AI analysis functionality.
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This script shows how to use the new async thread analysis function.
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"""
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import os
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import sys
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# Add the src directory to the path
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
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from database import (
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SessionLocal,
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Thread,
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analyze_and_update_threads,
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create_db_tables,
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get_threads_needing_analysis,
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)
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def main():
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"""Main function to test the AI analysis."""
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# Create database tables if they don't exist
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create_db_tables()
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# Example account email - replace with your actual account
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account_email = "your-email@example.com"
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# Get a database session
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db = SessionLocal()
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try:
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# Check how many threads need analysis
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threads_needing_analysis = get_threads_needing_analysis(db, account_email)
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print(
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f"Found {len(threads_needing_analysis)} threads needing analysis for {account_email}"
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)
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if not threads_needing_analysis:
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print(
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"No threads need analysis. Make sure you have ingested some emails first."
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)
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# Show all threads for this account
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all_threads = (
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db.query(Thread)
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.filter(Thread.account_email == account_email.lower())
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.all()
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)
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print(f"Total threads for {account_email}: {len(all_threads)}")
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if all_threads:
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print("Sample threads:")
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for thread in all_threads[:3]:
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print(
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f" Thread {thread.id}: {thread.subject} (analyzed: {thread.last_analyzed_at is not None})"
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)
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return
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print(f"Starting AI analysis for {len(threads_needing_analysis)} threads...")
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# Run the analysis with max 3 concurrent tasks
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analyze_and_update_threads(
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account_email=account_email, max_concurrent=3, only_unanalyzed=True
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)
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print("Analysis complete!")
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# Show results
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analyzed_threads = (
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db.query(Thread)
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.filter(
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Thread.account_email == account_email.lower(),
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Thread.last_analyzed_at.isnot(None),
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)
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.all()
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)
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print(f"\nAnalyzed {len(analyzed_threads)} threads:")
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for thread in analyzed_threads[:5]: # Show first 5
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print(f" Thread {thread.id}: {thread.subject[:50]}...")
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print(f" Actionable: {thread.actionable}")
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print(f" Confidence: {thread.ai_confidence:.2f}")
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print(f" Summary: {thread.ai_summary[:100]}...")
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print()
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except Exception as e:
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print(f"Error: {e}")
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import traceback
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traceback.print_exc()
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finally:
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db.close()
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if __name__ == "__main__":
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main()
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