- Added USB device detection and monitoring capabilities. - Updated SSH usage patterns to reflect dynamic host configurations. - Introduced automatic system discovery from journal logs, including OS detection and system profiling. - Enhanced configuration file intelligence with semantic search and categorization. - Expanded knowledge base structure and automatic learning processes. - Clarified the architecture and key modules for better understanding of system components.
467 lines
18 KiB
Markdown
467 lines
18 KiB
Markdown
# Macha Autonomous System - Design Document
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> **⚠️ IMPORTANT - READ THIS FIRST**
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> **FOR AI ASSISTANT**: This document is YOUR reference guide when modifying Macha's code.
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> - **ALWAYS consult this BEFORE refactoring** to ensure you don't remove existing capabilities
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> - **CHECK this when adding features** to avoid conflicts
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> - **UPDATE this document** when new capabilities are added
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> - **DO NOT DELETE ANYTHING FROM THIS DOCUMENT**
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> - During major refactors, you MUST verify each capability listed here is preserved
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## Overview
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Macha is an AI-powered autonomous system administrator capable of monitoring, maintaining, and managing multiple NixOS hosts in the infrastructure.
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## Core Capabilities
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### 1. Local System Management
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- Monitor system health (CPU, memory, disk, services)
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- Read and analyze logs via `journalctl`
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- Check service status and restart failed services
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- Execute system commands (with safety restrictions)
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- Monitor and repair Nix store corruption
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- Hardware awareness (CPU, GPU, network, storage)
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- USB device detection and monitoring
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### 2. Multi-Host Management via SSH
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**Macha CAN and SHOULD use SSH to manage other hosts.**
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#### SSH Access
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- **CRITICAL**: All command patterns defined in `command_patterns.py` (SINGLE SOURCE OF TRUTH)
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- Always uses explicit SSH key path: `-i /var/lib/macha/.ssh/id_ed25519`
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- All SSH commands automatically include the `-i` flag with absolute key path
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- Remote commands always prefixed with `sudo`
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- Runs as `macha` user (UID 2501) for standard operations
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- **Note**: Some internal operations (like remote monitoring) may use `root` SSH for privileged access
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- **DO NOT DUPLICATE these patterns elsewhere** - import from `command_patterns.py`
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- Has `NOPASSWD` sudo access for administrative commands
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- Shares SSH keys with other hosts in the infrastructure
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- Can SSH to any hosts defined in your NixOS flake configuration
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#### SSH Usage Patterns
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1. **Direct diagnostic commands:**
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```bash
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ssh hostname systemctl status service-name
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ssh hostname df -h
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```
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- Commands automatically transformed by the tools layer
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- Full command: `ssh -i /var/lib/macha/.ssh/id_ed25519 -o StrictHostKeyChecking=no macha@hostname sudo systemctl status service-name`
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- SSH key path is always explicit, commands are automatically prefixed with `sudo`
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2. **Status checks:**
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- Check service health on remote hosts
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- Gather system metrics
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- Review logs
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- Monitor resource usage
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3. **File operations:**
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- Use `scp` to copy files between hosts
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- Read configuration files on remote systems
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#### When to use SSH vs nh
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- **SSH**: For diagnostics, status checks, log review, quick commands
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- **nh remote deployment**: For applying NixOS configuration changes
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- `nh os switch -u --target-host=hostname --hostname=hostname`
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- Builds locally, deploys to remote host
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- Use for permanent configuration changes
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### 3. Automatic System Discovery
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#### Discovery from Journal Logs
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- Monitors `systemd-journal-remote` logs for new systems sending logs
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- Parses `_HOSTNAME` field from remote journal entries
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- Automatically converts short hostnames to FQDNs (`.coven.systems`)
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- Discovers systems within configurable time windows (default: 10 minutes)
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#### OS Detection
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- Detects operating system via SSH (`/etc/os-release`, `uname`)
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- Supports: NixOS, Ubuntu, Debian, Arch, Fedora, RHEL, Alpine, macOS, FreeBSD
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- Falls back to generic "linux" if specific distro cannot be determined
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- Records OS type in system registry for appropriate management strategies
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#### System Profiling
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- Automatically gathers system information upon discovery:
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- Running services (via `systemctl list-units`)
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- Hardware info (CPU cores, memory)
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- Capabilities (containers, web-server, database, remote-access)
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- System role determination (ai-workstation, server, workstation, minimal)
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- Registers discovered systems in ChromaDB context database
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- Sends notification when new systems are discovered
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### 4. NixOS Configuration Management
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#### Local Changes
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- Can propose changes to NixOS configuration
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- Requires human approval before applying
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- Uses `nh os switch` for local updates
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#### Remote Deployment
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- Can deploy to other hosts using `nh` with `--target-host`
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- Builds configuration locally (on Macha)
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- Pushes to remote system
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- Can take up to 1 hour for complex builds
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- **IMPORTANT**: Be patient with long-running builds, don't retry prematurely
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### 5. Configuration File Intelligence (RAG)
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#### Semantic Configuration Search
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- NixOS configuration files indexed in ChromaDB for semantic search
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- Query configurations by natural language: "gotify configuration", "journald settings"
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- CLI tools: `macha-configs <query>` and `macha-configs-read <path>`
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- Relevance scoring helps find the right config files quickly
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- Supports filtering by system hostname or category
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#### Configuration Categories
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- `apps/` - Application configurations (Gotify, Nextcloud, etc.)
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- `systems/` - Per-host system configurations
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- `osconfigs/` - Operating system level settings
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- `users/` - User management configurations
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#### Git Context Analysis
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- Tracks recent changes to configuration files via `git_context.py`
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- Correlates config changes with system behavior
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- Provides context when investigating issues after deployments
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- Helps understand "what changed" when debugging
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### 6. Hardware Awareness
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#### Local Hardware Detection
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- CPU: `lscpu` via `nix-shell -p util-linux`
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- GPU: `lspci` via `nix-shell -p pciutils`
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- Network: `lsblk`, `ip addr`
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- Storage: `df -h`, `lsblk`
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- USB devices: `lsusb`
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#### GPU Metrics
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- AMD GPUs: Try `rocm-smi`, sysfs (`/sys/class/drm/card*/device/`)
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- NVIDIA GPUs: Try `nvidia-smi`
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- Fallback: `sensors` for temperature data
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- Queries: temperature, utilization, clock speeds, power usage
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### 7. Ollama Queue System
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#### Architecture
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- **File-based queue**: `/var/lib/macha/queues/ollama/`
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- **Queue worker**: `ollama-queue-worker.service` (runs as `macha` user)
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- **Purpose**: Serialize all LLM requests to prevent resource contention
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#### Request Flow
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1. Any user (including regular users) → Write request to `pending/`
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2. Queue worker → Process requests serially (FIFO with priority)
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3. Queue worker → Write response to `completed/`
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4. Original requester → Read response from `completed/`
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#### Priority Levels
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- `INTERACTIVE` (0): User requests via `macha-chat`, `macha-ask`
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- `AUTONOMOUS` (1): Background maintenance checks
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- `BATCH` (2): Low-priority bulk operations
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#### Large Output Handling
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- Outputs >8KB: Split into chunks for hierarchical processing
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- Each chunk ~8KB (~2000 tokens)
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- Process chunks serially with progress feedback
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- Generate chunk summaries → meta-summary
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- Full outputs cached in `/var/lib/macha/tool_cache/`
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### 8. Knowledge Base & Learning
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#### ChromaDB Architecture
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- **Service**: ChromaDB runs as a standalone service on port 8000
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- **Storage**: Data persisted at `/var/lib/chromadb`
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- **Frontend**: `context_db.py` provides structured Python interface to ChromaDB
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- **Connection**: HTTP client to `localhost:8000`
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#### ChromaDB Collections
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1. **systems**: Infrastructure topology, registered hosts, OS types
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2. **relationships**: System dependencies and relationships
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3. **issues**: Historical problems and resolutions
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4. **decisions**: AI decisions and outcomes
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5. **config_files**: NixOS configuration files for RAG
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6. **knowledge**: Operational wisdom learned from experience
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#### Automatic Learning & Reflection
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- After successful operations, Macha automatically reflects via `reflect_and_learn()`
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- Extracts 1-2 specific, actionable learnings from each successful operation
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- Stores: topic, knowledge content, category, confidence level
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- Categories: command, pattern, troubleshooting, performance, general
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- Retrieved automatically when relevant to current tasks
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- Use `macha-knowledge` CLI to view/manage/search
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- Use `seed_knowledge.py` to populate initial operational knowledge
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### 9. Notifications
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#### Gotify Integration
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- Can send notifications via `macha-notify` command
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- Tool: `send_notification(title, message, priority)`
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#### Priority Levels
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- `2` (Low/Info): Routine status updates, completed tasks
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- `5` (Medium/Attention): Important events, configuration changes
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- `8` (High/Critical): Service failures, critical errors, security issues
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#### When to Notify
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- Critical service failures
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- Successful completion of major operations
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- Configuration changes that may affect users
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- Security-related events
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- New system discoveries
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- When explicitly requested by user
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### 10. Safety & Constraints
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#### Command Restrictions
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**Allowed Commands** (see `tools.py` for full list):
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- System management: `systemctl`, `journalctl`, `nh`, `nixos-rebuild`
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- Monitoring: `free`, `df`, `uptime`, `ps`, `top`, `ip`, `ss`
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- Hardware: `lscpu`, `lspci`, `lsblk`, `lshw`, `dmidecode`
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- Remote: `ssh`, `scp`
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- Power: `reboot`, `shutdown`, `poweroff` (use cautiously!)
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- File ops: `cat`, `ls`, `grep`
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- Network: `ping`, `dig`, `nslookup`, `curl`, `wget`
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- Logging: `logger`
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**NOT Allowed**:
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- Direct package modifications (`nix-env`, `nix profile`)
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- Destructive file operations (`rm -rf`, `dd`)
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- User management outside of NixOS config
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- Direct editing of system files (use NixOS config instead)
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#### Critical Services
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**Never disable or stop:**
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- SSH (network access)
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- Networking (connectivity)
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- systemd (system management)
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- Boot-related services
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#### Approval Required
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- Reboots or system power changes
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- Major configuration changes
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- Disabling any service
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- Changes to multiple hosts
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#### Interactive Discussion
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- `macha-approve discuss <N>` enables interactive Q&A about proposed actions
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- Implemented via `conversation.py` module
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- Users can ask follow-up questions before approving/rejecting
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- Provides detailed explanations and reasoning
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- Commands: `approve`, `reject`, `exit` to control flow
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### 11. Nix Store Maintenance
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#### Verification & Repair
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- Command: `nix-store --verify --check-contents --repair`
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- **WARNING**: Can take 30+ minutes to several hours
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- Only use when corruption is suspected
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- Not for routine maintenance
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- Verifies all store paths, repairs corrupted files
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#### Garbage Collection
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- Automatic via system configuration
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- Can be triggered manually with approval
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- Frees disk space by removing unused derivations
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### 12. Conversational Behavior
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#### Distinguish Requests from Acknowledgments
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- "Thanks" / "Thank you" → Acknowledgment (don't re-execute)
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- "Can you..." / "Please..." → Request (execute)
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- "What is..." / "How do..." → Question (answer)
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#### Tool Calling
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- Don't repeat tool calls unnecessarily
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- If a tool succeeds, don't run it again unless asked
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- Use cached results when available (`retrieve_cached_output`)
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#### Context Management
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- Be aware of token limits
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- Use hierarchical processing for large outputs
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- Prune conversation history intelligently
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- Cache and summarize when needed
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## Infrastructure Topology
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### Managed Hosts
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- **Self**: Main autonomous system running Macha
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- **Configured hosts**: Systems defined in your NixOS flake
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- **Auto-discovered hosts**: Additional systems detected via journal logs
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### Shared Configuration
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- All hosts share root SSH keys (for `nh` remote deployment)
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- `macha` user (UID 2501) exists on all managed hosts
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- Common NixOS configuration via flake
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- Multi-OS support: NixOS, Ubuntu, Debian, Arch, macOS, and others
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## Service Ecosystem
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### Core Services on Macha
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- `ollama.service`: LLM inference engine
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- `ollama-queue-worker.service`: Request serialization
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- `macha-autonomous.service`: Autonomous monitoring loop
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- `chromadb.service`: Vector database for context and knowledge (port 8000)
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### State Directories
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- `/var/lib/macha/`: Main state directory (0755, macha:macha)
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- `/var/lib/macha/queues/`: Queue directories (0777 for multi-user)
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- `/var/lib/macha/tool_cache/`: Cached tool outputs (0777)
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- `/var/lib/macha/logs/`: Log files and closed issues archive
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- `/var/lib/chromadb/`: ChromaDB vector database storage
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## CLI Tools
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- `macha-chat`: Interactive chat with tool calling
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- `macha-ask`: Single-question interface
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- `macha-check`: Trigger immediate health check
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- `macha-approve`: Approve pending actions
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- `macha-approve list` - Show pending actions
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- `macha-approve discuss <N>` - Interactive Q&A about action N
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- `macha-approve approve <N>` - Approve action N
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- `macha-approve reject <N>` - Reject action N
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- `macha-logs`: View autonomous service logs
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- `macha-issues`: Query issue database
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- `macha-knowledge`: Query knowledge base
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- `macha-systems`: List managed systems
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- `macha-configs`: Semantic search for configuration files
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- `macha-configs-read`: Read full configuration file content
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- `macha-notify`: Send Gotify notification
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## Architecture & Key Modules
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### Core Modules
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#### `agent.py` - AI Agent
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- Interfaces with Ollama LLM for reasoning
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- Implements tool calling with `tools.py`
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- Manages conversation history and context
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- Automatic learning via `reflect_and_learn()`
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- Supports queue-based and direct API modes
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#### `orchestrator.py` - Main Control Loop
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- Continuous monitoring and health checks
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- Coordinates all other components
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- Manages check intervals and autonomy levels
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- Initializes system registry and configuration parsing
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- Handles system discovery and registration
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#### `executor.py` - Safe Action Execution
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- Manages approval queue for actions
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- Respects autonomy levels (observe, suggest, auto-safe, auto-full)
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- Executes approved actions with safety checks
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- Logs all actions and outcomes
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#### `tools.py` - System Administration Tools
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- Defines all available tools for the AI agent
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- Command allow-list for safe mode
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- Executes system commands, reads files, checks services
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- Implements hardware queries and GPU metrics
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- Integrates with `command_patterns.py` for SSH
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#### `command_patterns.py` - SSH Command Patterns
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- **SINGLE SOURCE OF TRUTH** for SSH commands
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- Builds SSH commands with correct key paths and options
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- Handles automatic sudo prefixing for remote commands
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- Provides `build_ssh_command()` and `build_scp_command()`
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#### `context_db.py` - ChromaDB Frontend
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- Structured interface to ChromaDB vector database
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- Manages 6 collections: systems, relationships, issues, decisions, config_files, knowledge
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- Implements semantic search for configurations and knowledge
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- Tracks system relationships and dependencies
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#### `monitor.py` - Local System Monitoring
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- Collects system health metrics (CPU, memory, disk)
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- Checks systemd services and recent errors
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- Monitors NixOS generations and Nix store size
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- Generates human-readable summaries
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#### `remote_monitor.py` - Remote System Monitoring
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- SSH-based monitoring of remote hosts
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- Collects resources, services, disk, network status
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- Verifies connectivity before operations
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- Uses `command_patterns.py` for SSH access
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#### `system_discovery.py` - Auto-Discovery
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- Discovers new systems from journal logs
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- Detects OS types via SSH probing
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- Profiles systems: services, hardware, capabilities
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- Determines system roles automatically
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#### `issue_tracker.py` - Issue Management
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- Creates, updates, resolves, and closes issues
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- Finds similar past issues
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- Auto-resolves issues when problems disappear
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- Archives closed issues to JSONL logs
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#### `notifier.py` - Gotify Integration
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- Sends notifications at appropriate priority levels
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- Special methods for common events (failures, discoveries, actions)
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- Fails gracefully if Gotify unavailable
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#### `ollama_queue.py` - Request Serialization
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- File-based queue at `/var/lib/macha/queues/ollama/`
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- Three priority levels: INTERACTIVE, AUTONOMOUS, BATCH
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- Prevents resource contention on LLM
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- Tracks request status: pending → processing → completed/failed
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#### `ollama_worker.py` - Queue Worker Daemon
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- Processes queue requests serially
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- Runs as systemd service `ollama-queue-worker.service`
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- Handles timeouts and failures gracefully
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#### `conversation.py` - Interactive Discussion
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- Implements `macha-approve discuss` feature
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- Enables Q&A about proposed actions
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- Maintains context during discussion
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- Helps users understand AI reasoning
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#### `config_parser.py` - Configuration File Parsing
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- Parses NixOS configuration files from git repository
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- Indexes configurations in ChromaDB for RAG
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- Categorizes by type: apps, systems, osconfigs, users
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#### `git_context.py` - Git Analysis
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- Tracks recent configuration changes
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- Provides context when debugging after deployments
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- Correlates config changes with system issues
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#### `journal_monitor.py` - Journal Log Monitoring
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- Monitors systemd journal for specific patterns
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- Triggers on error conditions
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- Feeds into auto-discovery system
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#### `seed_knowledge.py` - Knowledge Seeding
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- Populates initial operational knowledge
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- Loads foundational patterns and commands
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- Run via `macha-knowledge seed`
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#### `chat.py` - Interactive Chat Interface
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- Implements `macha-chat` and `macha-ask` commands
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- Manages conversation state
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- Integrates with queue system for LLM requests
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#### `module.nix` - NixOS Module
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- Defines all configuration options
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- Creates systemd services (macha-autonomous, ollama-queue-worker, chromadb)
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- Sets up users, permissions, state directories
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- Provides all CLI tool wrappers
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## Philosophy & Principles
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1. **KISS (Keep It Simple, Stupid)**: Use existing NixOS options, avoid custom wrappers
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2. **Verify first**: Check source code/documentation before acting
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3. **Safety first**: Never break critical services, always require approval for risky changes
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4. **Learn continuously**: Extract and store operational knowledge
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5. **Multi-host awareness**: Macha manages the entire infrastructure, not just herself
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6. **User-friendly**: Clear communication, appropriate notifications
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7. **Patience**: Long-running operations (builds, repairs) can take an hour - don't panic
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8. **Tool reuse**: Use existing, verified tools instead of writing custom scripts
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## Future Capabilities (Not Yet Implemented)
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- [ ] Automatic security updates across all hosts
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- [ ] Predictive failure detection
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- [ ] Resource optimization recommendations
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- [ ] Integration with other communication platforms
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- [ ] Multi-agent coordination between hosts
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- [ ] Automated testing before deployment
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