LLM-Powered-Monitoring-Agent/PROGRESS.md

Project Progress

Phase 1: Initial Setup

1. Create monitor_agent.py
2. Create config.py
3. Create requirements.txt
4. Create README.md
5. Create .gitignore
6. Create SPEC.md
7. Create PROMPT.md
8. Create CONSTRAINTS.md

Phase 2: Data Storage

9. Create data_storage.py
10. Implement data storage functions in data_storage.py
11. Update monitor_agent.py to use data storage
12. Update SPEC.md to reflect data storage functionality

Phase 3: Expanded Monitoring

13. Implement CPU temperature monitoring
14. Implement GPU temperature monitoring
15. Implement system login attempt monitoring
16. Update monitor_agent.py to include new metrics
17. Update SPEC.md to reflect new metrics
18. Extend calculate_baselines to include system temps

Phase 4: Troubleshooting

19. Investigated and resolved issue with jc library
20. Removed jc library as a dependency
21. Implemented manual parsing of sensors command output

Tasks Already Done

[x] Ensure we aren't using mockdata for get_system_logs() and get_network_metrics() [x] Improve get_system_logs() to read new lines since last check [x] Improve get_network_metrics() by using a library like pingparsing [x] Ensure we are including CONSTRAINTS.md in our analyze_data_with_llm() function [x] Summarize entire report into a single sentence to said to Home Assistant [x] Figure out why Home Assitant isn't using the speaker

Keeping track of Current Objectives

[x] Improve "high" priority detection by explicitly instructing LLM to output severity in structured JSON format. [x] Implement dynamic contextual information (Known/Resolved Issues Feed) for LLM to improve severity detection.

Network Scanning (Nmap Integration)

1. Add python-nmap to requirements.txt and install.
2. Define NMAP_TARGETS and NMAP_SCAN_OPTIONS in config.py.
3. Create a new function get_nmap_scan_results() in monitor_agent.py:
   • Use python-nmap to perform a scan on the defined targets with the specified options.
   • Return the parsed results.
4. Integrate get_nmap_scan_results() into the main monitoring loop:
   • Call this function periodically (e.g., less frequently than other metrics).
   • Add the nmap results to the combined_data dictionary.
5. Update data_storage.py to store nmap results.
6. Extend calculate_baselines() in data_storage.py to include nmap baselines:
   • Compare current nmap results with historical data to identify changes.
7. Modify analyze_data_with_llm() prompt to include nmap scan results for analysis.
8. Consider how to handle nmap permissions.