added niri

This commit is contained in:
Geir Okkenhaug Jerstad 2025-06-10 20:33:54 +02:00
parent cdbce471ba
commit 8029d93a84
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@ -72,6 +72,13 @@ Deploy-rs uses a declarative configuration format in your flake:
}
```
```sh
# This is highly advised by deploy-rs
checks = builtins.mapAttrs (
system: deployLib: deployLib.deployChecks inputs.self.deploy
) inputs.deploy-rs.lib;
```
## Command Examples
```bash

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research/taskmaster-ai.md Normal file
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# Claude Task Master Research & Integration Plan
## Project Overview
**Claude Task Master** (https://github.com/eyaltoledano/claude-task-master) is an AI-powered task management system that leverages Claude's capabilities for intelligent task breakdown, prioritization, and execution tracking.
### Key Features Analysis
#### Core Capabilities
- **Intelligent Task Breakdown**: Automatically decomposes complex projects into manageable subtasks
- **Context-Aware Planning**: Uses AI to understand project requirements and dependencies
- **Progress Tracking**: Monitors task completion and adjusts plans dynamically
- **Natural Language Interface**: Allows task management through conversational commands
- **Integration Ready**: Designed to work with existing development workflows
#### Technical Architecture
- **Backend**: Node.js/Python-based task orchestration
- **AI Integration**: Claude API for task analysis and planning
- **Storage**: JSON/Database for task persistence
- **API**: RESTful endpoints for external integrations
## Workflow Compatibility Assessment
### Current Home-lab Methodology Alignment
#### ✅ Strong Fits
1. **Infrastructure-as-Code Philosophy**
- Task Master's structured approach aligns with your NixOS configuration management
- Can track infrastructure changes as tasks with dependencies
2. **Service-Oriented Architecture**
- Fits well with your microservices approach (Transmission, monitoring, etc.)
- Can manage service deployment and configuration tasks
3. **Documentation-Driven Development**
- Integrates with your markdown-based documentation workflow
- Can auto-generate task documentation and progress reports
#### ⚠️ Considerations
1. **Resource Overhead**
- Additional service to manage in your infrastructure
- API rate limits for Claude integration
2. **Data Privacy**
- Task data would be processed by Claude API
- Need to ensure sensitive infrastructure details are handled appropriately
## Integration Strategy
### Phase 1: Core Installation & Setup
#### Prerequisites
```bash
# Dependencies for Home-lab integration
- Node.js runtime environment
- Claude API access (Anthropic)
- Docker/Podman for containerization
- NixOS service configuration
```
#### Installation Plan
1. **Clone and Setup**
```bash
cd /home/geir/Home-lab/services
git clone https://github.com/eyaltoledano/claude-task-master.git taskmaster
cd taskmaster
```
2. **NixOS Service Configuration**
- Create `taskmaster.nix` service definition
- Configure API keys and environment variables
- Set up reverse proxy through existing nginx setup
3. **Environment Configuration**
```env
CLAUDE_API_KEY=<your-key>
TASKMASTER_PORT=3001
DATABASE_URL=sqlite:///mnt/storage/taskmaster.db
```
### Phase 2: GitHub Copilot Integration
#### Integration Points
1. **Code Task Generation**
- Use Copilot to generate coding tasks from repository analysis
- Automatic task creation from GitHub issues and PRs
2. **Development Workflow Enhancement**
```typescript
// Example integration hook
interface CopilotTaskBridge {
generateTasksFromCode(filePath: string): Task[];
updateTaskProgress(taskId: string, codeChanges: CodeDiff[]): void;
suggestNextSteps(currentTask: Task): Suggestion[];
}
```
3. **VS Code Extension Development**
- Custom extension to bridge Copilot suggestions with Task Master
- Real-time task updates based on code changes
### Phase 3: Context7 MCP Integration
#### Model Context Protocol Benefits
1. **Unified Context Management**
- Task Master tasks as context for Claude conversations
- Project state awareness across all AI interactions
2. **Cross-Service Communication**
```json
{
"mcp_config": {
"services": {
"taskmaster": {
"endpoint": "http://sleeper-service:3001/api",
"capabilities": ["task_management", "progress_tracking"]
},
"github_copilot": {
"integration": "vscode_extension",
"context_sharing": true
}
}
}
}
```
3. **Context Flow Architecture**
```
GitHub Copilot → Context7 MCP → Task Master → Claude API
↑ ↓
VS Code Editor ←─────── Task Updates ←─────── AI Insights
```
## Implementation Roadmap
### Week 1: Foundation
- [ ] Set up Task Master on sleeper-service
- [ ] Configure basic NixOS service
- [ ] Test Claude API integration
- [ ] Create initial task templates for Home-lab projects
### Week 2: GitHub Integration
- [ ] Develop Copilot bridge extension
- [ ] Set up GitHub webhook integration
- [ ] Create automated task generation from repository events
- [ ] Test code-to-task mapping
### Week 3: MCP Integration
- [ ] Implement Context7 MCP protocol support
- [ ] Create unified context sharing system
- [ ] Develop cross-service communication layer
- [ ] Test end-to-end workflow
### Week 4: Optimization & Documentation
- [ ] Performance tuning and monitoring
- [ ] Complete integration documentation
- [ ] Create user workflow guides
- [ ] Set up backup and recovery procedures
## NixOS Service Configuration Preview
```nix
# /home/geir/Home-lab/machines/sleeper-service/services/taskmaster.nix
{ config, pkgs, ... }:
{
services.taskmaster = {
enable = true;
port = 3001;
user = "sma";
group = "users";
environmentFile = "/etc/taskmaster/env";
dataDir = "/mnt/storage/taskmaster";
};
# Nginx reverse proxy configuration
services.nginx.virtualHosts."taskmaster.home-lab" = {
locations."/" = {
proxyPass = "http://localhost:3001";
proxyWebsockets = true;
};
};
# Firewall configuration
networking.firewall.allowedTCPPorts = [ 3001 ];
}
```
## Benefits for Home-lab Workflow
### Immediate Improvements
1. **Project Visibility**: Clear overview of all infrastructure tasks and their status
2. **Dependency Management**: Automatic tracking of service dependencies and update sequences
3. **Documentation Automation**: AI-generated task documentation and progress reports
4. **Workflow Optimization**: Intelligent task prioritization based on system state
### Long-term Value
1. **Knowledge Retention**: Comprehensive history of infrastructure decisions and changes
2. **Onboarding**: New team members can quickly understand project structure through task history
3. **Compliance**: Automated tracking for security updates and maintenance tasks
4. **Scalability**: Framework for managing larger infrastructure deployments
## Risk Assessment & Mitigation
### Technical Risks
- **API Dependencies**: Mitigate with local fallback modes
- **Data Loss**: Regular backups to /mnt/storage/backups
- **Performance Impact**: Resource monitoring and limits
### Security Considerations
- **API Key Management**: Use NixOS secrets management
- **Network Isolation**: Restrict external API access through firewall rules
- **Data Encryption**: Encrypt sensitive task data at rest
## Conclusion
Claude Task Master shows strong alignment with your Home-lab methodology and could significantly enhance project management capabilities. The integration with GitHub Copilot and Context7 MCP would create a powerful AI-assisted development environment that maintains context across all project activities.
**Recommendation**: Proceed with implementation, starting with Phase 1 to establish the foundation and evaluate real-world performance in your environment.