# Project Progress

## Phase 1: Initial Setup

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

## Phase 2: Data Storage

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

## Phase 3: Expanded Monitoring

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

## Phase 4: Troubleshooting

19. [x] Investigated and resolved issue with `jc` library
20. [x] Removed `jc` library as a dependency
21. [x] 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.