chore: consolidate Syslog Solution code into unified repository structure
- Moved scattered scripts, templates, and documentation into organized directories (applications/, scripts/, assets/). - Updated .gitignore to strictly exclude secrets, state files, and IDE configs. - Added comprehensive README.md outlining repository structure and best practices. - Preserved all existing documentation and technical architecture files. - Prepared infrastructure/ for AWS Org and Proxmox Terraform management.
This commit is contained in:
@@ -0,0 +1,74 @@
|
|||||||
|
name: Documentation Validation
|
||||||
|
|
||||||
|
on:
|
||||||
|
push:
|
||||||
|
branches: [ main ]
|
||||||
|
paths:
|
||||||
|
- 'documentation/**'
|
||||||
|
- 'README.md'
|
||||||
|
pull_request:
|
||||||
|
branches: [ main ]
|
||||||
|
paths:
|
||||||
|
- 'documentation/**'
|
||||||
|
- 'README.md'
|
||||||
|
|
||||||
|
jobs:
|
||||||
|
validate-docs:
|
||||||
|
runs-on: ubuntu-latest
|
||||||
|
|
||||||
|
steps:
|
||||||
|
- uses: actions/checkout@v3
|
||||||
|
|
||||||
|
- name: Check for broken links
|
||||||
|
run: |
|
||||||
|
# Install link checker
|
||||||
|
pip install linkchecker
|
||||||
|
|
||||||
|
# Check documentation links
|
||||||
|
find documentation/ -name "*.md" -exec linkchecker --check-extern {} \;
|
||||||
|
|
||||||
|
- name: Validate markdown structure
|
||||||
|
run: |
|
||||||
|
# Check for required documentation sections
|
||||||
|
echo "Validating documentation structure..."
|
||||||
|
|
||||||
|
# Check root README
|
||||||
|
if [ ! -f "README.md" ]; then
|
||||||
|
echo "❌ Missing root README.md"
|
||||||
|
exit 1
|
||||||
|
fi
|
||||||
|
|
||||||
|
# Check documentation directory exists
|
||||||
|
if [ ! -d "documentation/" ]; then
|
||||||
|
echo "❌ Missing documentation/ directory"
|
||||||
|
exit 1
|
||||||
|
fi
|
||||||
|
|
||||||
|
echo "✅ Documentation structure validation passed"
|
||||||
|
|
||||||
|
- name: Run markdown lint
|
||||||
|
uses: DavidAnson/markdownlint-cli2-action@v9
|
||||||
|
with:
|
||||||
|
globs: 'documentation/**/*.md README.md'
|
||||||
|
|
||||||
|
terraform-validation:
|
||||||
|
runs-on: ubuntu-latest
|
||||||
|
if: contains(github.event.head_commit.message, 'terraform') || contains(github.event.head_commit.message, 'infrastructure')
|
||||||
|
|
||||||
|
steps:
|
||||||
|
- uses: actions/checkout@v3
|
||||||
|
|
||||||
|
- name: Setup Terraform
|
||||||
|
uses: hashicorp/setup-terraform@v2
|
||||||
|
with:
|
||||||
|
terraform_version: 1.5.0
|
||||||
|
|
||||||
|
- name: Terraform Format
|
||||||
|
id: fmt
|
||||||
|
run: terraform fmt -check -recursive infrastructure/
|
||||||
|
|
||||||
|
- name: Terraform Init
|
||||||
|
run: terraform init infrastructure/aws-org/
|
||||||
|
|
||||||
|
- name: Terraform Validate
|
||||||
|
run: terraform validate infrastructure/aws-org/
|
||||||
@@ -85,3 +85,5 @@ Desktop.ini
|
|||||||
# Project specific
|
# Project specific
|
||||||
.hermes/
|
.hermes/
|
||||||
hermes-workspace/
|
hermes-workspace/
|
||||||
|
*.pyc
|
||||||
|
__pycache__/
|
||||||
|
|||||||
@@ -1,164 +1,44 @@
|
|||||||
# Syslog Solution LLC - Unified Repository
|
# Syslog Solution LLC - Master Repository
|
||||||
|
|
||||||
## 🏢 About Syslog Solution LLC
|
## Overview
|
||||||
|
This repository serves as the central source of truth for all Syslog Solution LLC code, documentation, and infrastructure configurations. It consolidates business strategy, technical architecture, client project templates, and automated tooling into a single, organized structure.
|
||||||
Syslog Solution LLC is a technology consulting firm specializing in:
|
|
||||||
- **AI Automation & Agent Development** - Custom AI workflows and multi-agent systems
|
|
||||||
- **Cloud Infrastructure** - AWS, Proxmox, and hybrid cloud solutions
|
|
||||||
- **Business Process Optimization** - Automation of repetitive tasks and workflows
|
|
||||||
- **Ghana Market Focus** - Localized solutions for Ghanaian businesses
|
|
||||||
|
|
||||||
## 📁 Repository Structure
|
|
||||||
|
|
||||||
This repository contains everything needed to run Syslog Solution LLC:
|
|
||||||
|
|
||||||
|
## Repository Structure
|
||||||
```
|
```
|
||||||
syslogsolution/
|
syslogsolution/
|
||||||
├── documentation/ # Business and technical documentation
|
├── documentation/ # Business strategy, client onboarding, and operational procedures
|
||||||
├── infrastructure/ # Infrastructure as Code (Terraform, Ansible)
|
├── infrastructure/ # Terraform configs (AWS Org), Proxmox cluster setups, and deployment scripts
|
||||||
├── customers/ # Customer projects and templates
|
├── applications/ # Python scripts, AI agent frameworks, whitepapers, and client analysis tools
|
||||||
├── scripts/ # Deployment and maintenance scripts
|
├── assets/ # Brand assets, logos, and SVG graphics
|
||||||
├── tests/ # Test suites and validation
|
└── scripts/ # Automation scripts, setup utilities, and maintenance tools
|
||||||
└── tools/ # Development tools and utilities
|
|
||||||
```
|
```
|
||||||
|
|
||||||
## 🚀 Quick Start
|
## Getting Started
|
||||||
|
1. **Clone the repository:**
|
||||||
|
```bash
|
||||||
|
git clone <local-path> ~/syslogsolution
|
||||||
|
```
|
||||||
|
2. **Review the documentation:**
|
||||||
|
- Start with `documentation/01-business-strategy/` for the business vision.
|
||||||
|
- Check `documentation/02-technical-architecture/` for infrastructure and AI agent setups.
|
||||||
|
3. **Infrastructure Setup:**
|
||||||
|
- Navigate to `infrastructure/aws-org/` for AWS Organization Terraform configs.
|
||||||
|
- Use `scripts/` for Proxmox and GPU setup utilities.
|
||||||
|
|
||||||
### For Team Members
|
## Security & Best Practices
|
||||||
1. **Read the documentation** - Start with `documentation/01-business-strategy/`
|
- **Never commit secrets:** The `.gitignore` strictly excludes `.env`, `.pem`, `.key`, and state files.
|
||||||
2. **Set up development environment** - Follow `documentation/05-development/`
|
- **Branching Strategy:** Use feature branches for new client projects or infrastructure changes.
|
||||||
3. **Review customer projects** - Check `customers/templates/` for examples
|
- **Documentation First:** All code changes should be accompanied by updated documentation.
|
||||||
|
|
||||||
### For Infrastructure Deployment
|
## Maintenance
|
||||||
```bash
|
- Regularly sync with the Hermes Agent workspace for automation scripts.
|
||||||
cd infrastructure/aws-org/
|
- Update the `infrastructure/` directory as the Proxmox cluster and AWS environment evolve.
|
||||||
terraform init
|
- Archive completed client projects in `documentation/` after onboarding.
|
||||||
terraform plan
|
|
||||||
terraform apply
|
|
||||||
```
|
|
||||||
|
|
||||||
### For Customer Project Creation
|
## Contact
|
||||||
```bash
|
For issues or contributions:
|
||||||
# Use the project template
|
- Email: jerome@sysloggh.com
|
||||||
cp -r customers/templates/ai-agent-basic/ customers/active/new-client-project/
|
- Telegram: @mejerome19
|
||||||
```
|
|
||||||
|
|
||||||
## 📚 Documentation Index
|
## License
|
||||||
|
Proprietary to Syslog Solution LLC. All rights reserved.
|
||||||
### Business Strategy (`documentation/01-business-strategy/`)
|
|
||||||
- Business vision and mission
|
|
||||||
- Market analysis and positioning
|
|
||||||
- Financial projections and pricing
|
|
||||||
- Pitch decks and marketing materials
|
|
||||||
|
|
||||||
### Technical Architecture (`documentation/02-technical-architecture/`)
|
|
||||||
- Infrastructure overview and diagrams
|
|
||||||
- AI agents framework documentation
|
|
||||||
- Deployment standards and procedures
|
|
||||||
- Security and compliance guidelines
|
|
||||||
|
|
||||||
### Operations (`documentation/03-operations/`)
|
|
||||||
- Client onboarding process
|
|
||||||
- Support and maintenance procedures
|
|
||||||
- Incident response and escalation
|
|
||||||
- Quality assurance and testing
|
|
||||||
|
|
||||||
### Customer Portal (`documentation/04-customer-portal/`)
|
|
||||||
- Getting started guides
|
|
||||||
- API documentation and examples
|
|
||||||
- FAQ and troubleshooting
|
|
||||||
- Service level agreements
|
|
||||||
|
|
||||||
### Development (`documentation/05-development/`)
|
|
||||||
- Coding standards and best practices
|
|
||||||
- Git workflow and branching strategy
|
|
||||||
- Testing framework and guidelines
|
|
||||||
- Deployment checklist
|
|
||||||
|
|
||||||
## 🛠️ Infrastructure
|
|
||||||
|
|
||||||
### AWS Organization (`infrastructure/aws-org/`)
|
|
||||||
- Complete AWS Organization setup with Terraform
|
|
||||||
- Multi-account structure (Management, Security, Workloads, Sandbox)
|
|
||||||
- IAM users, groups, and policies
|
|
||||||
- Billing alerts and monitoring
|
|
||||||
|
|
||||||
### Proxmox Cluster (`infrastructure/proxmox/`)
|
|
||||||
- Homelab infrastructure automation
|
|
||||||
- GPU passthrough configuration
|
|
||||||
- Backup and recovery procedures
|
|
||||||
- Network and storage configuration
|
|
||||||
|
|
||||||
### AI Platform (`infrastructure/ai-platform/`)
|
|
||||||
- AWS Bedrock and SageMaker setup
|
|
||||||
- RAG (Retrieval Augmented Generation) pipelines
|
|
||||||
- Multi-agent orchestration
|
|
||||||
- Model deployment and monitoring
|
|
||||||
|
|
||||||
## 👥 Customer Management
|
|
||||||
|
|
||||||
### Project Templates (`customers/templates/`)
|
|
||||||
- **ai-agent-basic/** - Basic AI agent implementation
|
|
||||||
- **data-pipeline/** - Data engineering and ETL pipelines
|
|
||||||
- **website-migration/** - Website migration and optimization
|
|
||||||
- **cloud-optimization/** - Cloud cost and performance optimization
|
|
||||||
|
|
||||||
### Active Projects (`customers/active/`)
|
|
||||||
- Current customer engagements
|
|
||||||
- Project documentation and status
|
|
||||||
- Delivery timelines and milestones
|
|
||||||
|
|
||||||
### Archived Projects (`customers/archived/`)
|
|
||||||
- Completed customer projects
|
|
||||||
- Lessons learned and case studies
|
|
||||||
- Reference implementations
|
|
||||||
|
|
||||||
## 🔧 Development Tools
|
|
||||||
|
|
||||||
### Scripts (`scripts/`)
|
|
||||||
- Deployment and provisioning scripts
|
|
||||||
- Monitoring and health checks
|
|
||||||
- Backup and maintenance utilities
|
|
||||||
- Environment setup scripts
|
|
||||||
|
|
||||||
### Tests (`tests/`)
|
|
||||||
- Infrastructure validation tests
|
|
||||||
- Integration and end-to-end tests
|
|
||||||
- Performance and load testing
|
|
||||||
- Security scanning
|
|
||||||
|
|
||||||
### Tools (`tools/`)
|
|
||||||
- Code generators and templates
|
|
||||||
- Migration and conversion utilities
|
|
||||||
- Local development environment
|
|
||||||
- Pre-commit hooks and linters
|
|
||||||
|
|
||||||
## 🤝 Contributing
|
|
||||||
|
|
||||||
### For Team Members
|
|
||||||
1. Follow the coding standards in `documentation/05-development/`
|
|
||||||
2. Use the git workflow described in the development documentation
|
|
||||||
3. Submit pull requests for review
|
|
||||||
4. Update documentation when making changes
|
|
||||||
|
|
||||||
### For External Contributors
|
|
||||||
This repository contains proprietary business information. External contributions are not currently accepted.
|
|
||||||
|
|
||||||
## 📞 Contact & Support
|
|
||||||
|
|
||||||
- **Business Email**: jerome@sysloggh.com
|
|
||||||
- **Technical Support**: @mejerome19 (Telegram)
|
|
||||||
- **Website**: https://sysloggh.com (Coming Soon)
|
|
||||||
- **Location**: Accra, Ghana
|
|
||||||
|
|
||||||
## ⚖️ License & Usage
|
|
||||||
|
|
||||||
This repository contains proprietary information of Syslog Solution LLC. All rights reserved.
|
|
||||||
|
|
||||||
Unauthorized copying, distribution, or use of this repository's contents is prohibited.
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
**Last Updated**: April 2026
|
|
||||||
**Version**: 1.0.0
|
|
||||||
**Maintained by**: Jerome Tabiri, Syslog Solution LLC
|
|
||||||
|
|||||||
@@ -0,0 +1,46 @@
|
|||||||
|
# 01 - Proxmox & VM Passthrough — Home
|
||||||
|
**Purpose:** Complete setup guide for Proxmox VM passthrough with optimal resource allocation.
|
||||||
|
|
||||||
|
## Topics Covered
|
||||||
|
|
||||||
|
- **GPU Passthrough:** Configure AMD/Intel/NVIDIA GPUs for VM access
|
||||||
|
- **NVMe Passthrough:** Pass NVMe drives to VMs for high I/O performance
|
||||||
|
- **USB Passthrough:** Connect USB devices (webcams, dongles, etc.) to VMs
|
||||||
|
- **Networking:** Bridge networking, VLANs, and virtual switches
|
||||||
|
- **Resource Allocation:** CPU cores, RAM, and storage optimization
|
||||||
|
|
||||||
|
## Related Guides
|
||||||
|
|
||||||
|
- **[00 - Proxmox & VM Passthrough](00 - Proxmox & VM Passthrough.md)** — This overview document
|
||||||
|
- **[03 - AMD GPU Passthrough](../03\ -\ AMD\ GPU\ Passthrough/)** — AMD-specific setup
|
||||||
|
|
||||||
|
## Quick Start
|
||||||
|
|
||||||
|
### Create a VM with GPU Passthrough
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Step 1: Find available GPU
|
||||||
|
rocm-smi | grep "GPU" # AMD
|
||||||
|
nvidia-smi # NVIDIA
|
||||||
|
|
||||||
|
# Step 2: Create VM with GPU passthrough
|
||||||
|
qm create 100 --name qwen-vm --memory 32768 --cores 8 --arch x86_64
|
||||||
|
qm set 100 --hostpci0=0000:03:00.0,pcie=1,x-vga=1 # AMD example
|
||||||
|
|
||||||
|
# Step 3: Install QEMU Guest Agent
|
||||||
|
apt install qemu-guest-agent
|
||||||
|
|
||||||
|
# Step 4: Reboot VM
|
||||||
|
qm reboot 100
|
||||||
|
```
|
||||||
|
|
||||||
|
## Best Practices
|
||||||
|
|
||||||
|
1. **IOMMU Groups:** Always check if devices are in separate IOMMU groups
|
||||||
|
2. **VFIO Modules:** Ensure `vfio-pci` module is loaded before boot
|
||||||
|
3. **PCIe Hotplug:** Disable for stability unless required
|
||||||
|
4. **Memory Ballooning:** Disable in VM for consistent performance
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
*This guide is essential for GPU passthrough to VMs running LLM inference workloads.*
|
||||||
@@ -0,0 +1,18 @@
|
|||||||
|
# 03 - AI AGENTS & LEARNING — Home
|
||||||
|
**Purpose:** AI agent frameworks, learning resources, and implementation guides.
|
||||||
|
|
||||||
|
## Contents
|
||||||
|
|
||||||
|
### **01 - Claude Code & Opencode** — Agent framework tutorials and best practices.
|
||||||
|
|
||||||
|
### **02 - OpenClaw Framework** — Open-source agent orchestration platform setup and usage.
|
||||||
|
|
||||||
|
### **03 - MCP (Model Context Protocol)** — Integration guides for connecting LLMs to external tools and data sources.
|
||||||
|
|
||||||
|
### **04 - Autonomous AI Agents** — Research and implementation of autonomous agent workflows.
|
||||||
|
|
||||||
|
### **05 - Agent Research & Learning** — Papers, YouTube tutorials, podcasts, and general learning resources.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
*This section pairs conceptual guides with their implementation scripts for rapid prototyping and deployment.*
|
||||||
@@ -0,0 +1,133 @@
|
|||||||
|
# 01 - BUSINESS & STRATEGY — Home
|
||||||
|
|
||||||
|
**Purpose:** Business strategy, market analysis, and growth planning for Syslog GH/LLC.
|
||||||
|
|
||||||
|
## Core Areas
|
||||||
|
|
||||||
|
### Customer Acquisition
|
||||||
|
- SMB-focused AI consulting (Discovery-first approach)
|
||||||
|
- Tech Edge Partnerships (AWS, GitHub, Cloudflare)
|
||||||
|
- Ghana market entry strategy
|
||||||
|
- LinkedIn organic growth campaigns
|
||||||
|
|
||||||
|
### Service Lines
|
||||||
|
- $299/mo AI Navigation Partner
|
||||||
|
- $399/mo AI Agent Deployment
|
||||||
|
- $1.5-5K Custom Implementation Projects
|
||||||
|
- 70-80% recurring revenue target
|
||||||
|
|
||||||
|
### Strategic Differentiators
|
||||||
|
- Privacy-focused AI (local deployment, minimal data collection)
|
||||||
|
- OpenMAIC education framework
|
||||||
|
- Brother co-founders (Jerome & Theodore) for dual expertise
|
||||||
|
- Open-source community positioning
|
||||||
|
|
||||||
|
### Target Markets
|
||||||
|
1. **Ghana:** AI adoption gap (65% SMB adoption, 87% data concerns)
|
||||||
|
2. **US:** Discovery-first AI services ($2.5B addressable market)
|
||||||
|
3. **Remote:** Distributed workforce support
|
||||||
|
|
||||||
|
### Competitive Landscape
|
||||||
|
- **Traditional IT Firms:** Lack AI expertise; high cost
|
||||||
|
- **Pure Play AI Agencies:** Overkill pricing ($10K+ minimums)
|
||||||
|
- **Freelancers:** Inconsistent quality, no ongoing support
|
||||||
|
- **Our Edge:** Balanced pricing, local context, privacy focus
|
||||||
|
|
||||||
|
## Financial Model
|
||||||
|
|
||||||
|
### Revenue Streams
|
||||||
|
1. **Monthly Retainers:** $299-399/mo (AI Navigation/Agent)
|
||||||
|
2. **Project Fees:** $1.5-5K (custom implementations)
|
||||||
|
3. **Training:** $500-2K (workshops, team upskilling)
|
||||||
|
4. **Partnerships:** Revenue share with tech partners
|
||||||
|
|
||||||
|
### Cost Structure
|
||||||
|
- **Personnel:** 70% (founder salaries, contractor fees)
|
||||||
|
- **Infrastructure:** 15% (AWS, Proxmox, software tools)
|
||||||
|
- **Marketing:** 10% (ads, content, partnerships)
|
||||||
|
- **Operations:** 5% (legal, accounting, admin)
|
||||||
|
|
||||||
|
### Projections (Year 1)
|
||||||
|
- **Q1:** $5K revenue (pilot projects, early adopters)
|
||||||
|
- **Q2:** $15K revenue (scaled services, referrals)
|
||||||
|
- **Q3:** $30K revenue (established pipeline, partnerships)
|
||||||
|
- **Q4:** $50K revenue (recurring revenue dominance)
|
||||||
|
- **Year 1 Total:** $100K revenue target
|
||||||
|
|
||||||
|
## Growth Strategy
|
||||||
|
|
||||||
|
### Phase 1: Foundation (Months 1-3)
|
||||||
|
- Complete 3 pilot projects
|
||||||
|
- Build case studies and testimonials
|
||||||
|
- Establish basic operational processes
|
||||||
|
- Secure 2-3 anchor clients
|
||||||
|
|
||||||
|
### Phase 2: Scale (Months 4-9)
|
||||||
|
- Hire first contractor/employee
|
||||||
|
- Systematize service delivery
|
||||||
|
- Expand to 10+ active clients
|
||||||
|
- Develop partner network
|
||||||
|
|
||||||
|
### Phase 3: Expand (Months 10-12)
|
||||||
|
- Add new service lines
|
||||||
|
- Explore product opportunities
|
||||||
|
- Consider geographic expansion
|
||||||
|
- Build team to 3-5 people
|
||||||
|
|
||||||
|
## Key Performance Indicators (KPIs)
|
||||||
|
|
||||||
|
### Financial KPIs
|
||||||
|
- Monthly Recurring Revenue (MRR)
|
||||||
|
- Customer Acquisition Cost (CAC)
|
||||||
|
- Lifetime Value (LTV)
|
||||||
|
- Gross Margin
|
||||||
|
|
||||||
|
### Operational KPIs
|
||||||
|
- Client Satisfaction Score (CSAT)
|
||||||
|
- Project Delivery Time
|
||||||
|
- First Contact Resolution Rate
|
||||||
|
- Employee Satisfaction
|
||||||
|
|
||||||
|
### Growth KPIs
|
||||||
|
- New Clients per Month
|
||||||
|
- Referral Rate
|
||||||
|
- Partnership Growth
|
||||||
|
- Market Share
|
||||||
|
|
||||||
|
## Risk Assessment
|
||||||
|
|
||||||
|
### High Risks
|
||||||
|
- **Market Timing:** AI adoption in Ghana slower than expected
|
||||||
|
- **Competition:** Larger firms entering the space
|
||||||
|
- **Talent:** Difficulty finding skilled AI practitioners
|
||||||
|
- **Cash Flow:** Irregular project-based income initially
|
||||||
|
|
||||||
|
### Mitigation Strategies
|
||||||
|
- **Diversify:** Mix of retainer and project work
|
||||||
|
- **Specialize:** Focus on privacy and local context
|
||||||
|
- **Partner:** Leverage tech partnerships for credibility
|
||||||
|
- **Buffer:** Maintain 6-month runway in reserves
|
||||||
|
|
||||||
|
## Next Steps
|
||||||
|
|
||||||
|
### Immediate (Next 30 Days)
|
||||||
|
1. Finalize service packaging and pricing
|
||||||
|
2. Create sales collateral and website updates
|
||||||
|
3. Identify and reach out to 10 potential pilot clients
|
||||||
|
4. Set up project management and communication systems
|
||||||
|
|
||||||
|
### Short-term (Next 90 Days)
|
||||||
|
1. Secure 3 pilot projects
|
||||||
|
2. Develop case study template
|
||||||
|
3. Establish partner referral program
|
||||||
|
4. Create basic training materials
|
||||||
|
|
||||||
|
### Medium-term (Next 6 Months)
|
||||||
|
1. Systematize onboarding process
|
||||||
|
2. Hire first support/development resource
|
||||||
|
3. Expand service offerings based on feedback
|
||||||
|
4. Build recurring revenue to 50% of total
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
*This document is a living strategy guide for Syslog Solution LLC. Review and update quarterly.*
|
||||||
@@ -0,0 +1,90 @@
|
|||||||
|
# 02 - TECHNICAL INFRASTRUCTURE — Overview
|
||||||
|
**Purpose:** Complete technical guide for Syslog infrastructure, GPU passthrough, and model deployment.
|
||||||
|
|
||||||
|
## Infrastructure Components
|
||||||
|
|
||||||
|
### **01 - Proxmox & VM Passthrough**
|
||||||
|
- GPU passthrough configuration (AMD/Intel)
|
||||||
|
- VM networking setup
|
||||||
|
- Resource allocation best practices
|
||||||
|
|
||||||
|
### **02 - GPU Monitoring**
|
||||||
|
- Grafana dashboards for GPU telemetry
|
||||||
|
- ROCm monitoring setup
|
||||||
|
- Real-time performance tracking
|
||||||
|
|
||||||
|
### **03 - AMD GPU Passthrough (Strix Halo)**
|
||||||
|
- Detailed AMD APU passthrough for host LLM access
|
||||||
|
- Vulkan driver configuration
|
||||||
|
- HIP SDK integration
|
||||||
|
|
||||||
|
### **04 - Qwen3.5 Model Setup**
|
||||||
|
- Qwen3.5-MoE (Mixture of Experts) installation
|
||||||
|
- Vulkan backend optimization
|
||||||
|
- Production inference configuration
|
||||||
|
|
||||||
|
### **05 - AWS Cloud Infrastructure**
|
||||||
|
|
||||||
|
### **06 - Troubleshooting**
|
||||||
|
- Common issues and resolutions
|
||||||
|
- Debugging methodology
|
||||||
|
- Emergency procedures
|
||||||
|
- VPC and networking architecture
|
||||||
|
- EC2 instance configuration for AI workloads
|
||||||
|
- S3 data pipeline setup
|
||||||
|
- Cost optimization strategies
|
||||||
|
|
||||||
|
## Deployment Standards
|
||||||
|
|
||||||
|
- **GPU Access:** AMD Strix Halo for host inference, NVIDIA for training
|
||||||
|
- **Model Hosting:** Ollama local deployment @ 192.168.68.8:8080
|
||||||
|
- **Cloud:** AWS for scalable cloud workloads
|
||||||
|
- **Storage:** S3 for model weights and datasets
|
||||||
|
- **Monitoring:** Grafana + Prometheus for observability
|
||||||
|
|
||||||
|
## Common Operations
|
||||||
|
|
||||||
|
### Start Qwen3.5-MoE
|
||||||
|
```bash
|
||||||
|
ollama pull qwen3.5:250b-moe
|
||||||
|
ollama serve --model qwen3.5:250b-moe
|
||||||
|
```
|
||||||
|
|
||||||
|
### Check GPU Status
|
||||||
|
```bash
|
||||||
|
# AMD
|
||||||
|
rocm-smi
|
||||||
|
watch -n 5 rocm-smi
|
||||||
|
|
||||||
|
# NVIDIA
|
||||||
|
nvidia-smi
|
||||||
|
watch -n 5 nvidia-smi
|
||||||
|
```
|
||||||
|
|
||||||
|
### Deploy New Agent
|
||||||
|
```bash
|
||||||
|
# Clone agent repository
|
||||||
|
git clone https://github.com/sysloggh/agent-template.git
|
||||||
|
cd agent-template
|
||||||
|
|
||||||
|
# Configure environment
|
||||||
|
cp .env.example .env
|
||||||
|
# Edit .env with API keys and settings
|
||||||
|
|
||||||
|
# Install dependencies
|
||||||
|
pip install -r requirements.txt
|
||||||
|
|
||||||
|
# Deploy
|
||||||
|
source venv/bin/activate
|
||||||
|
python main.py
|
||||||
|
```
|
||||||
|
|
||||||
|
## Related Documentation
|
||||||
|
|
||||||
|
- [Business Strategy](../01\ -\ BUSINESS\ \&\ STRATEGY/00\ -\ Business Strategy Home.md)
|
||||||
|
- [AI Agents Framework](../03\ -\ AI\ AGENTS\ \&\ LEARNING/00\ -\ AI Agents Learning Home.md)
|
||||||
|
- [Operational Excellence](../05\ -\ OPERATIONAL\ EXCELLENCE/00\ -\ Operational Excellence Home.md)
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
*This section pairs implementation guides with their respective scripts for rapid deployment.*
|
||||||
@@ -0,0 +1,82 @@
|
|||||||
|
# Documentation Migration Summary
|
||||||
|
|
||||||
|
## Current Status
|
||||||
|
- **Last Updated:** 2026-05-02 18:16:00
|
||||||
|
- **Total Graph Nodes:** 171
|
||||||
|
- **Total Graph Edges:** 117
|
||||||
|
- **Documentation Files Processed:** 29 (excluding this summary)
|
||||||
|
- **Migration Status:** COMPLETE — All source files accounted for
|
||||||
|
|
||||||
|
## Migration History
|
||||||
|
|
||||||
|
### Batch 1 (April 27, 2026)
|
||||||
|
- Migrated core documentation files
|
||||||
|
- Created ~25 nodes for business strategy, technical architecture, operations
|
||||||
|
- Total nodes at completion: ~138
|
||||||
|
|
||||||
|
### Batch 2 (May 1, 2026)
|
||||||
|
- Migrated templates and additional technical docs
|
||||||
|
- Created ~42 nodes
|
||||||
|
- Total nodes at completion: ~160
|
||||||
|
|
||||||
|
### Batch 3 (May 2, 2026)
|
||||||
|
- Migrated AI agents framework documentation
|
||||||
|
- Created 8 new nodes:
|
||||||
|
- #180: Business Strategy & Vision — Home
|
||||||
|
- #181: Technical Architecture — Overview
|
||||||
|
- #182: Autonomous AI Agents — Home
|
||||||
|
- #183: Claude Code & Opencode — Home
|
||||||
|
- #184: MCP (Model Context Protocol) — Home
|
||||||
|
- #185: OpenClaw Framework — Home
|
||||||
|
- #186: OpenMAIC Education — Home
|
||||||
|
- #187: Qwen3.5 Model Setup — Home
|
||||||
|
- Total nodes at completion: 168
|
||||||
|
|
||||||
|
### Batch 4 (May 2, 2026 — Cron Check)
|
||||||
|
- Ran full deduplication audit against graph
|
||||||
|
- Verified all 29 source files have matching nodes in graph
|
||||||
|
- **0 new nodes needed** — migration complete
|
||||||
|
- Total nodes now: 169 (includes 1 non-documentation node added independently)
|
||||||
|
|
||||||
|
### Batch 5 (May 2, 2026 — Evening Cron Validation)
|
||||||
|
- Full deduplication audit re-run
|
||||||
|
- **0 new documentation nodes needed** — all 29 files still accounted for
|
||||||
|
- Total nodes now: 171 (2 additional non-documentation nodes: relay messages, audit logs)
|
||||||
|
- **Stale content detected** (requires manual review):
|
||||||
|
- Node #163 (Technical Infrastructure): Ollama reference → should be llama.cpp
|
||||||
|
- Node #187 (Qwen3.5 Model Setup): Ollama reference + CUDA-only → should include ROCm for AMD GPU
|
||||||
|
- **Limitation:** Native API (3000) does not support PATCH for node updates — stale content fixes require full node replacement or manual intervention
|
||||||
|
|
||||||
|
## Files Migrated by Category
|
||||||
|
|
||||||
|
| Category | Files | Status |
|
||||||
|
|----------|-------|--------|
|
||||||
|
| 01-business-strategy | 2 | ✅ Migrated |
|
||||||
|
| 02-technical-architecture | 14 | ✅ Migrated |
|
||||||
|
| 03-operations | 4 | ✅ Migrated |
|
||||||
|
| 04-customer-portal | 1 | ✅ Migrated |
|
||||||
|
| 05-development | 1 | ✅ Migrated |
|
||||||
|
| templates | 7 | ✅ Migrated |
|
||||||
|
| **Total** | **29** | **COMPLETE** |
|
||||||
|
|
||||||
|
## Deduplication Method
|
||||||
|
- Path-based deduplication using `metadata.source_file`
|
||||||
|
- Title-based deduplication abandoned (unreliable due to heading changes)
|
||||||
|
- All 29 source files verified against existing graph nodes
|
||||||
|
|
||||||
|
## Validation
|
||||||
|
- Live system validation performed before each migration batch
|
||||||
|
- Proxmox cluster health checked
|
||||||
|
- VM and storage inventories verified
|
||||||
|
- GPU assignments confirmed (acerpve=RTX 3090, amdpve=AMD Strix Halo 395)
|
||||||
|
|
||||||
|
## Stale Content Findings (May 2, 2026)
|
||||||
|
- **Node #163** (Technical Infrastructure Overview): Contains "Ollama" reference — should be "llama.cpp"
|
||||||
|
- **Node #187** (Qwen3.5 Model Setup): Contains "Ollama" reference AND CUDA-only mention — should include ROCm for AMD Strix Halo GPU
|
||||||
|
- **Action Required:** Manual review and update of these nodes (API limitation prevents automated PATCH)
|
||||||
|
|
||||||
|
## Notes
|
||||||
|
- No new documentation files detected since last migration
|
||||||
|
- Graph growing due to non-documentation content (relay messages, audits, lessons)
|
||||||
|
- Next scheduled check: weekly cron
|
||||||
|
- **API Limitation:** Native API (3000) supports POST for creation but not PATCH for updates. MCP bridge (3100) `createNode` returns 404. Node updates require full replacement or manual intervention.
|
||||||
@@ -0,0 +1,124 @@
|
|||||||
|
# 06 - TROUBLESHOOTING — Home
|
||||||
|
**Purpose:** Common issues, error resolutions, and debugging guides for Syslog infrastructure.
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
|
||||||
|
This section provides solutions for common technical problems across the Syslog infrastructure stack. Each guide includes symptoms, root causes, and step-by-step fixes.
|
||||||
|
|
||||||
|
## Troubleshooting Categories
|
||||||
|
|
||||||
|
### **Proxmox & Virtualization**
|
||||||
|
- VM won't start or crashes
|
||||||
|
- GPU passthrough failures
|
||||||
|
- Network connectivity issues
|
||||||
|
- Storage performance problems
|
||||||
|
- Resource allocation errors
|
||||||
|
|
||||||
|
### **GPU & Hardware**
|
||||||
|
- AMD GPU detection failures
|
||||||
|
- ROCm driver installation issues
|
||||||
|
- Temperature and cooling problems
|
||||||
|
- Performance degradation
|
||||||
|
- Compatibility issues
|
||||||
|
|
||||||
|
### **AWS Cloud**
|
||||||
|
- EC2 instance connectivity
|
||||||
|
- S3 bucket access errors
|
||||||
|
- VPC networking issues
|
||||||
|
- Cost overrun alerts
|
||||||
|
- Security group misconfigurations
|
||||||
|
|
||||||
|
### **AI Agents & Models**
|
||||||
|
- Model loading failures
|
||||||
|
- Inference performance issues
|
||||||
|
- Agent communication errors
|
||||||
|
- API connectivity problems
|
||||||
|
- Memory allocation errors
|
||||||
|
|
||||||
|
### **Networking & Security**
|
||||||
|
- Firewall blocking issues
|
||||||
|
- DNS resolution failures
|
||||||
|
- SSL/TLS certificate problems
|
||||||
|
- Authentication errors
|
||||||
|
- Rate limiting and throttling
|
||||||
|
|
||||||
|
## Troubleshooting Methodology
|
||||||
|
|
||||||
|
### **Step 1: Gather Information**
|
||||||
|
- Error messages and logs
|
||||||
|
- System status and metrics
|
||||||
|
- Recent changes or updates
|
||||||
|
- User reports and symptoms
|
||||||
|
|
||||||
|
### **Step 2: Isolate the Problem**
|
||||||
|
- Reproduce the issue
|
||||||
|
- Identify affected components
|
||||||
|
- Check dependencies and connections
|
||||||
|
- Verify configurations
|
||||||
|
|
||||||
|
### **Step 3: Diagnose Root Cause**
|
||||||
|
- Check logs and monitoring
|
||||||
|
- Test individual components
|
||||||
|
- Compare with known working state
|
||||||
|
- Identify configuration drift
|
||||||
|
|
||||||
|
### **Step 4: Apply Fix**
|
||||||
|
- Implement solution
|
||||||
|
- Test thoroughly
|
||||||
|
- Document the fix
|
||||||
|
- Update monitoring alerts
|
||||||
|
|
||||||
|
### **Step 5: Prevent Recurrence**
|
||||||
|
- Update documentation
|
||||||
|
- Add monitoring checks
|
||||||
|
- Create automation scripts
|
||||||
|
- Train team members
|
||||||
|
|
||||||
|
## Quick Reference
|
||||||
|
|
||||||
|
### **Common Commands**
|
||||||
|
```bash
|
||||||
|
# Check system logs
|
||||||
|
journalctl -xe --no-pager | tail -100
|
||||||
|
|
||||||
|
# Check GPU status
|
||||||
|
rocm-smi
|
||||||
|
nvidia-smi
|
||||||
|
|
||||||
|
# Check network connectivity
|
||||||
|
ping -c 4 8.8.8.8
|
||||||
|
traceroute google.com
|
||||||
|
|
||||||
|
# Check disk space
|
||||||
|
df -h
|
||||||
|
du -sh /path/to/directory
|
||||||
|
|
||||||
|
# Check running processes
|
||||||
|
top -b -n 1 | head -20
|
||||||
|
ps aux | grep -i process_name
|
||||||
|
```
|
||||||
|
|
||||||
|
### **Log Locations**
|
||||||
|
- **Proxmox:** `/var/log/pve/`
|
||||||
|
- **System:** `/var/log/syslog`, `/var/log/messages`
|
||||||
|
- **GPU:** `/var/log/kern.log` (dmesg)
|
||||||
|
- **AWS:** CloudWatch Logs
|
||||||
|
- **Applications:** Application-specific log directories
|
||||||
|
|
||||||
|
## Emergency Procedures
|
||||||
|
|
||||||
|
### **Critical Issues**
|
||||||
|
1. **Service Down:** Check status, restart if needed, investigate root cause
|
||||||
|
2. **Data Loss:** Stop writes, assess backup, restore from backup
|
||||||
|
3. **Security Breach:** Isolate system, preserve logs, investigate scope
|
||||||
|
4. **Performance Crisis:** Throttle traffic, scale resources, optimize
|
||||||
|
|
||||||
|
### **Contact Escalation**
|
||||||
|
- **Level 1:** System administrators
|
||||||
|
- **Level 2:** Technical lead
|
||||||
|
- **Level 3:** External support (vendor, consultant)
|
||||||
|
- **Level 4:** Emergency response team
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
*This troubleshooting guide is a living document. Update it with new issues and solutions as they are discovered.*
|
||||||
@@ -0,0 +1,54 @@
|
|||||||
|
1|# 05 - Agent Research & Learning — Home
|
||||||
|
2|**Purpose:** Research papers, tutorials, and resources for AI agent development.
|
||||||
|
3|
|
||||||
|
4|## Overview
|
||||||
|
5|
|
||||||
|
6|Stay current with the latest developments in AI agent technology through curated research, tutorials, and community resources.
|
||||||
|
7|
|
||||||
|
8|## Learning Resources
|
||||||
|
9|
|
||||||
|
10|### **Academic Papers**
|
||||||
|
11|- **Multi-Agent Systems:** Foundations and applications
|
||||||
|
12|- **Reinforcement Learning for Agents:** Q-learning, PPO, GRPO
|
||||||
|
13|- **Agent Communication Protocols:** FIPA, ACL, custom protocols
|
||||||
|
14|- **Tool Learning:** In-context learning for tool selection
|
||||||
|
15|
|
||||||
|
16|### **Video Tutorials**
|
||||||
|
17|- **YouTube Series:** Deep dives into agent architectures
|
||||||
|
18|- **Conference Keynotes:** NeurIPS, ICML, ICLR talks
|
||||||
|
19|- **Hands-on Labs:** Step-by-step implementation guides
|
||||||
|
20|
|
||||||
|
21|### **Podcasts**
|
||||||
|
22|- **AI Agent Deep Dives:** Interviews with researchers
|
||||||
|
23|- **Industry Applications:** Real-world use cases
|
||||||
|
24|- **Future Trends:** Expert predictions and analysis
|
||||||
|
25|
|
||||||
|
26|### **Community Resources**
|
||||||
|
27|- **GitHub Repositories:** Open-source agent frameworks
|
||||||
|
28|- **Discord Servers:** Community support and collaboration
|
||||||
|
29|- **Conferences:** Annual meetups and workshops
|
||||||
|
30|
|
||||||
|
31|## Recommended Reading
|
||||||
|
32|
|
||||||
|
33|1. **"Language Models as Zero-Shot Planners"** — arXiv:2106.04415
|
||||||
|
34|2. **"ReAct: Synergizing Reasoning and Acting"** — arXiv:2210.03629
|
||||||
|
35|3. **"Tool Learning: LLMs Learning to Call External APIs"** — arXiv:2302.04762
|
||||||
|
36|4. **"Multi-Agent Collaboration: A Survey"** — arXiv:2310.08056
|
||||||
|
37|
|
||||||
|
38|## Stay Updated
|
||||||
|
39|
|
||||||
|
40|- **arXiv Alerts:** Set up daily/weekly digests for "agent" papers
|
||||||
|
41|- **Twitter/X:** Follow key researchers and AI labs
|
||||||
|
42|- **GitHub Topics:** #ai-agents, #multi-agent, #agent-orchestration
|
||||||
|
43|- **Newsletter:** AI Weekly, Towards Data Science, ML News
|
||||||
|
44|
|
||||||
|
45|## Related Frameworks
|
||||||
|
46|
|
||||||
|
47|- **[Claude Code & Opencode](../01\ -\ Claude\ Code\ \&\ Opencode/)** — Practical implementation
|
||||||
|
48|- **[OpenClaw Framework](../02\ -\ OpenClaw\ Framework/)** — Production orchestration
|
||||||
|
49|- **[OpenMAIC Education](../06\ -\ OpenMAIC\ Education/)** — Structured learning
|
||||||
|
50|
|
||||||
|
51|---
|
||||||
|
52|
|
||||||
|
53|*Continuous learning resources for Jerome & Theodore to stay ahead in AI agent development.*
|
||||||
|
54|
|
||||||
@@ -0,0 +1,55 @@
|
|||||||
|
# 03 - AMD GPU Passthrough (Strix Halo) — Home
|
||||||
|
**Purpose:** Detailed AMD APU passthrough configuration for host LLM access.
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
|
||||||
|
This guide covers the complete setup for AMD Strix Halo GPU passthrough, enabling native LLM inference on AMD hardware.
|
||||||
|
|
||||||
|
## What You'll Learn
|
||||||
|
|
||||||
|
- **Hardware preparation:** Verify Strix Halo compatibility
|
||||||
|
- **BIOS configuration:** Enable IOMMU and PCIe passthrough
|
||||||
|
- **Kernel configuration:** Load VFIO modules properly
|
||||||
|
- **Proxmox setup:** Configure GPU for VM passthrough
|
||||||
|
- **Driver installation:** Vulkan, ROCm, HIP SDK integration
|
||||||
|
- **Qwen3.5-MoE setup:** Configure for AMD GPU acceleration
|
||||||
|
|
||||||
|
## Prerequisites
|
||||||
|
|
||||||
|
- AMD Strix Halo APU with integrated Radeon graphics
|
||||||
|
- Linux system kernel 5.4+ with IOMMU support
|
||||||
|
- Proxmox VE 7.x or later
|
||||||
|
- 16GB+ system RAM (8GB for APU graphics, 8GB for OS)
|
||||||
|
- SSD storage for VM images
|
||||||
|
|
||||||
|
## Quick Start
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Enable IOMMU in GRUB
|
||||||
|
# Edit /etc/default/grub, add:
|
||||||
|
# GRUB_CMDLINE_LINUX="amd_iommu=on iommu=pt"
|
||||||
|
|
||||||
|
# Update GRUB
|
||||||
|
update-grub
|
||||||
|
|
||||||
|
# Load VFIO modules
|
||||||
|
echo "vfio
|
||||||
|
vfio_iommu_type1
|
||||||
|
vfio_pci
|
||||||
|
vfio_virqfd" | sudo tee /etc/modules-load.d/vfio.conf
|
||||||
|
|
||||||
|
# Blacklist Radeon in VM
|
||||||
|
modprobe -r radeon amdgpu
|
||||||
|
|
||||||
|
# Reboot to apply changes
|
||||||
|
reboot
|
||||||
|
```
|
||||||
|
|
||||||
|
## Related Guides
|
||||||
|
|
||||||
|
- **[01 - Proxmox & VM Passthrough](../01\ -\ Proxmox\ \&\ VM\ Passthrough/)** — General passthrough setup
|
||||||
|
- **[04 - Qwen3.5 Model Setup](../04\ -\ Qwen3.5\ Model\ Setup/)** — Model deployment
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
*Essential for running Qwen3.5-MoE locally on AMD hardware with Vulkan backend acceleration.*
|
||||||
@@ -0,0 +1,70 @@
|
|||||||
|
1|# 04 - Autonomous AI Agents — Home
|
||||||
|
2|**Purpose:** Research and implementation of autonomous agent workflows.
|
||||||
|
3|
|
||||||
|
4|## Overview
|
||||||
|
5|
|
||||||
|
6|Autonomous AI agents can execute multi-step tasks independently, learn from experience, and make decisions based on context. This section covers advanced orchestration patterns for production-grade agent systems.
|
||||||
|
7|
|
||||||
|
8|## Key Capabilities
|
||||||
|
9|
|
||||||
|
10|### **Multi-Agent Collaboration**
|
||||||
|
11|- Role-based agent delegation
|
||||||
|
12|- Cross-agent memory sharing
|
||||||
|
13|- Conflict resolution protocols
|
||||||
|
14|- Distributed task execution
|
||||||
|
15|
|
||||||
|
16|### **Autonomous Behaviors**
|
||||||
|
17|- Self-correction loops
|
||||||
|
18|- Error recovery mechanisms
|
||||||
|
19|- Performance optimization
|
||||||
|
20|- Adaptive resource allocation
|
||||||
|
21|
|
||||||
|
22|### **Advanced Patterns**
|
||||||
|
23|- Agent swarms (10+ coordinated agents)
|
||||||
|
24|- Continuous learning cycles
|
||||||
|
25|- Human-in-the-loop intervention points
|
||||||
|
26|- Audit trails and observability
|
||||||
|
27|
|
||||||
|
28|## Implementation Strategies
|
||||||
|
29|
|
||||||
|
30|### **Sequential Workflows**
|
||||||
|
31|```python
|
||||||
|
32|agent1.run(task="Research market")
|
||||||
|
33|agent2.run(task="Analyze data")
|
||||||
|
34|agent3.run(task="Generate report")
|
||||||
|
35|```
|
||||||
|
36|
|
||||||
|
37|### **Parallel Workflows**
|
||||||
|
38|```python
|
||||||
|
39|results = await asyncio.gather(
|
||||||
|
40| agent1.run(task="A"),
|
||||||
|
41| agent2.run(task="B"),
|
||||||
|
42| agent3.run(task="C")
|
||||||
|
43|)
|
||||||
|
44|```
|
||||||
|
45|
|
||||||
|
46|### **Feedback Loops**
|
||||||
|
47|```python
|
||||||
|
48|while not agent.is_satisfied(result):
|
||||||
|
49| agent.improve(result)
|
||||||
|
50| result = agent.execute(prompt)
|
||||||
|
51|```
|
||||||
|
52|
|
||||||
|
53|## Use Cases
|
||||||
|
54|
|
||||||
|
55|- Market research automation
|
||||||
|
56|- Multi-step data analysis pipelines
|
||||||
|
57|- Customer support orchestration
|
||||||
|
58|- Content generation workflows
|
||||||
|
59|- Codebase refactoring agents
|
||||||
|
60|
|
||||||
|
61|## Related Frameworks
|
||||||
|
62|
|
||||||
|
63|- **[OpenClaw](../02\ -\ OpenClaw\ Framework/)** — Agent orchestration platform
|
||||||
|
64|- **[MCP](../03\ -\ MCP\ \(Model\ Context\ Protocol\)/)** — Tool integration layer
|
||||||
|
65|- **[OpenMAIC](../06\ -\ OpenMAIC\ Education/)** — Educational resources
|
||||||
|
66|
|
||||||
|
67|---
|
||||||
|
68|
|
||||||
|
69|*Advanced agent patterns for Jerome & Theodore's complex automation projects.*
|
||||||
|
70|
|
||||||
@@ -0,0 +1,43 @@
|
|||||||
|
# 05 - AWS Cloud Infrastructure — Home
|
||||||
|
**Purpose:** AWS architecture, networking, and cost optimization for AI workloads.
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
|
||||||
|
This section covers our AWS cloud infrastructure setup for scalable AI services, including:
|
||||||
|
- VPC networking architecture
|
||||||
|
- EC2 instance optimization for GPU workloads
|
||||||
|
- S3 data pipeline automation
|
||||||
|
- Cost optimization strategies
|
||||||
|
|
||||||
|
## Infrastructure Components
|
||||||
|
|
||||||
|
### **AWS Architecture**
|
||||||
|
- **US-East-1 (N. Virginia):** Primary production environment
|
||||||
|
- **Multi-AZ deployment:** High availability for critical services
|
||||||
|
- **VPC networking:** Isolated subnets for compute, storage, and monitoring
|
||||||
|
|
||||||
|
### **Compute Resources**
|
||||||
|
- **p4d.24xlarge:** A100-based instances for training
|
||||||
|
- **g5.xlarge:** A10 instances for inference
|
||||||
|
- **m5.large:** CPU-based instances for web services
|
||||||
|
- **Spot instances:** Cost savings for non-critical workloads
|
||||||
|
|
||||||
|
### **Storage**
|
||||||
|
- **S3 buckets:** Model weights, datasets, backup archives
|
||||||
|
- **EBS volumes:** High-performance storage for active VMs
|
||||||
|
- **Glacier:** Cold storage for historical data
|
||||||
|
|
||||||
|
## Cost Optimization
|
||||||
|
|
||||||
|
- **Reserved Instances:** 1-3 year commitments for baseline workloads
|
||||||
|
- **Spot Instances:** 70% savings for fault-tolerant tasks
|
||||||
|
- **S3 Lifecycle Policies:** Automatic tiering to Glacier
|
||||||
|
- **CloudWatch Alarms:** Budget alerts and anomaly detection
|
||||||
|
|
||||||
|
## Related Documents
|
||||||
|
|
||||||
|
- **[Qwen3.5-MoE Setup](../02\ -\ TECHNICAL\ INFRASTRUCTURE/04\ -\ Qwen3.5\ Model\ Setup/)** — Model deployment strategies
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
*Our AWS infrastructure supports our SMB AI services and agent deployments with maximum efficiency.*
|
||||||
@@ -0,0 +1,53 @@
|
|||||||
|
1|# 01 - Claude Code & Opencode — Home
|
||||||
|
2|**Purpose:** Agent framework tutorials and best practices for Claude Code and OpenCode CLI.
|
||||||
|
3|
|
||||||
|
4|## Overview
|
||||||
|
5|
|
||||||
|
6|This section provides practical guides for deploying and managing AI coding agents using Claude Code and OpenCode CLI tools.
|
||||||
|
7|
|
||||||
|
8|## Contents
|
||||||
|
9|
|
||||||
|
10|### **Claude Code**
|
||||||
|
11|- Quick start and configuration
|
||||||
|
12|- Integration with IDEs
|
||||||
|
13|- Custom agent definitions
|
||||||
|
14|- Security best practices
|
||||||
|
15|
|
||||||
|
16|### **OpenCode**
|
||||||
|
17|- CLI setup and usage
|
||||||
|
18|- Extending with custom commands
|
||||||
|
19|- Multi-agent orchestration
|
||||||
|
20|- Production deployment patterns
|
||||||
|
21|
|
||||||
|
22|### **Best Practices**
|
||||||
|
23|- Context window management
|
||||||
|
24|- Agent sandboxing rules
|
||||||
|
25|- Error handling patterns
|
||||||
|
26|- Performance optimization
|
||||||
|
27|
|
||||||
|
28|## Quick Start
|
||||||
|
29|
|
||||||
|
30|```bash
|
||||||
|
31|# Install OpenCode CLI
|
||||||
|
32|pip install opencode-cli
|
||||||
|
33|
|
||||||
|
34|# Configure API keys
|
||||||
|
35|export OPENAI_API_KEY="***"
|
||||||
|
36|
|
||||||
|
37|# Run Claude Code
|
||||||
|
38|opencode run "Analyze this codebase for security issues"
|
||||||
|
39|
|
||||||
|
40|# Create custom agent
|
||||||
|
41|opencode agent create --name my-helper --template best-practices
|
||||||
|
42|```
|
||||||
|
43|
|
||||||
|
44|## Related Frameworks
|
||||||
|
45|
|
||||||
|
46|- **[MCP (Model Context Protocol)](../03\ -\ MCP\ \(Model\ Context\ Protocol\)/)** — Tool integration
|
||||||
|
47|- **[OpenClaw Framework](../02\ -\ OpenClaw\ Framework/)** — Multi-agent orchestration
|
||||||
|
48|- **[Autonomous AI Agents](../04\ -\ Autonomous\ AI\ Agents/)** — Advanced workflows
|
||||||
|
49|
|
||||||
|
50|---
|
||||||
|
51|
|
||||||
|
52|*Practical guides for Jerome & Theodore to implement AI coding agents in their daily workflow.*
|
||||||
|
53|
|
||||||
@@ -0,0 +1,51 @@
|
|||||||
|
1|# 02 - GPU Monitoring — Home
|
||||||
|
2|**Purpose:** Grafana dashboards and monitoring setup for GPU telemetry.
|
||||||
|
3|
|
||||||
|
4|## Contents
|
||||||
|
5|
|
||||||
|
6|This directory contains:
|
||||||
|
7|- Grafana dashboard configuration
|
||||||
|
8|- ROCm monitoring setup
|
||||||
|
9|- Real-time performance tracking
|
||||||
|
10|
|
||||||
|
11|### Monitoring Features
|
||||||
|
12|
|
||||||
|
13|- **Real-time GPU utilization:** Track VRAM, compute, and memory usage
|
||||||
|
14|- **Temperature monitoring:** Alert on overheating conditions
|
||||||
|
15|- **Performance metrics:** Core clock, power consumption, fan speeds
|
||||||
|
16|- **Historical data:** Grafana time-series graphs for trend analysis
|
||||||
|
17|
|
||||||
|
18|## Quick Start
|
||||||
|
19|
|
||||||
|
20|### Grafana Dashboard Setup
|
||||||
|
21|
|
||||||
|
22|```bash
|
||||||
|
23|# Install Grafana
|
||||||
|
24|sudo apt install grafana
|
||||||
|
25|
|
||||||
|
26|# Start Grafana service
|
||||||
|
27|systemctl start grafana-server
|
||||||
|
28|
|
||||||
|
29|# Access dashboard
|
||||||
|
30|# http://localhost:3000 (admin/admin)
|
||||||
|
31|```
|
||||||
|
32|
|
||||||
|
33|### ROCm Monitoring
|
||||||
|
34|
|
||||||
|
35|```bash
|
||||||
|
36|# Install ROCm health monitoring tools
|
||||||
|
37|sudo apt install rocminfo rocm-smi
|
||||||
|
38|
|
||||||
|
39|# Real-time monitoring
|
||||||
|
40|watch -n 1 rocm-smi
|
||||||
|
41|```
|
||||||
|
42|
|
||||||
|
43|## Related Infrastructure
|
||||||
|
44|
|
||||||
|
45|- **[AMD GPU Passthrough](../03\ -\ AMD\ GPU\ Passthrough/)** — Hardware configuration
|
||||||
|
46|- **[Qwen3.5 Model Setup](../04\ -\ Qwen3.5\ Model\ Setup/)** — Model deployment
|
||||||
|
47|
|
||||||
|
48|---
|
||||||
|
49|
|
||||||
|
50|*Monitor your GPUs 24/7 to ensure optimal performance for LLM inference workloads.*
|
||||||
|
51|
|
||||||
@@ -0,0 +1,87 @@
|
|||||||
|
1|# 02 - MCP (Model Context Protocol) — Home
|
||||||
|
2|**Purpose:** MCP integration guides and implementation examples.
|
||||||
|
3|
|
||||||
|
4|## What is MCP?
|
||||||
|
5|Model Context Protocol (MCP) is a standardized interface for connecting LLMs to external tools, data sources, and services.
|
||||||
|
6|
|
||||||
|
7|## MCP Benefits
|
||||||
|
8|- **Unified interface** for tool integration
|
||||||
|
9|- **Hot-swappable** tool providers
|
||||||
|
10|- **Standardized** input/output schemas
|
||||||
|
11|- **Type-safe** API definitions
|
||||||
|
12|
|
||||||
|
13|## Core Concepts
|
||||||
|
14|
|
||||||
|
15|### Tools
|
||||||
|
16|External capabilities exposed to the model:
|
||||||
|
17|- File system access
|
||||||
|
18|- Database queries
|
||||||
|
19|- API endpoints
|
||||||
|
20|- Custom business logic
|
||||||
|
21|
|
||||||
|
22|### Resources
|
||||||
|
23|Data sources the model can read:
|
||||||
|
24|- Documents
|
||||||
|
25|- Configuration files
|
||||||
|
26|- Real-time data feeds
|
||||||
|
27|- Knowledge bases
|
||||||
|
28|
|
||||||
|
29|### Prompts
|
||||||
|
30|Pre-defined interaction templates:
|
||||||
|
31|- Task initiation patterns
|
||||||
|
32|- System prompt variations
|
||||||
|
33|- Role-definition templates
|
||||||
|
34|
|
||||||
|
35|## Quick Start
|
||||||
|
36|
|
||||||
|
37|```bash
|
||||||
|
38|# Install MCP server
|
||||||
|
39|pip install mcp-server-filesystem mcp-server-sqlite
|
||||||
|
40|
|
||||||
|
41|# Start a filesystem MCP server
|
||||||
|
42|mcp-server-filesystem --path /path/to/allowed/directory
|
||||||
|
43|
|
||||||
|
44|# Connect via client
|
||||||
|
45|from mcp import ClientSession, StdioServerParameters
|
||||||
|
46|
|
||||||
|
47|async with ClientSession(
|
||||||
|
48| stdio_server_parameters=StdioServerParameters(
|
||||||
|
49| command="mcp-server-filesystem",
|
||||||
|
50| args=["--path", "/path/to/allowed/directory"]
|
||||||
|
51| )
|
||||||
|
52|) as session:
|
||||||
|
53| # List available tools
|
||||||
|
54| tools = await session.list_tools()
|
||||||
|
55|```
|
||||||
|
56|
|
||||||
|
57|## Available MCP Servers
|
||||||
|
58|
|
||||||
|
59|- **Filesystem:** Access documents and configuration files
|
||||||
|
60|- **SQL databases:** Query relational databases safely
|
||||||
|
61|- **API Gateway:** Connect to REST/GraphQL endpoints
|
||||||
|
62|- **Custom Business Logic:** Integrate internal tools and services
|
||||||
|
63|
|
||||||
|
64|## Security Considerations
|
||||||
|
65|
|
||||||
|
66|- **Path whitelisting:** Only allow specific directories
|
||||||
|
67|- **Query rate limiting:** Prevent resource exhaustion
|
||||||
|
68|- **Input sanitization:** Validate all user inputs
|
||||||
|
69|- **Token-based access:** Require authentication for sensitive operations
|
||||||
|
70|
|
||||||
|
71|## Use Cases
|
||||||
|
72|
|
||||||
|
73|- **Document analysis:** Read and process large document collections
|
||||||
|
74|- **Database queries:** Extract insights from operational databases
|
||||||
|
75|- **API orchestration:** Coordinate across multiple external services
|
||||||
|
76|- **Code generation:** Write and execute code safely
|
||||||
|
77|
|
||||||
|
78|## References
|
||||||
|
79|
|
||||||
|
80|- [MCP Specification](https://modelcontextprotocol.io)
|
||||||
|
81|- [MCP Server Implementations](https://github.com/modelcontextprotocol/servers)
|
||||||
|
82|- [Integration Examples](../03%20-%20AI%20AGENTS%20&%20LEARNING/02%20-%20OpenClaw%20Framework/)
|
||||||
|
83|
|
||||||
|
84|---
|
||||||
|
85|
|
||||||
|
86|*MCP integrates seamlessly with OpenClaw agent orchestration for scalable AI applications.*
|
||||||
|
87|
|
||||||
@@ -0,0 +1,59 @@
|
|||||||
|
1|# OpenClaw Framework — Home
|
||||||
|
2|**Purpose:** Complete guide to setting up and using the OpenClaw agent orchestration framework.
|
||||||
|
3|
|
||||||
|
4|## What is OpenClaw?
|
||||||
|
5|OpenClaw provides a powerful framework for orchestrating AI agents, enabling multi-agent collaboration, task delegation, and complex workflow automation.
|
||||||
|
6|
|
||||||
|
7|## Quick Start
|
||||||
|
8|
|
||||||
|
9|### Installation
|
||||||
|
10|```bash
|
||||||
|
11|# Clone the repository
|
||||||
|
12|git clone https://github.com/openclaw/openclaw.git
|
||||||
|
13|cd openclaw
|
||||||
|
14|
|
||||||
|
15|# Install dependencies
|
||||||
|
16|pip install -r requirements.txt
|
||||||
|
17|
|
||||||
|
18|# Configure API keys
|
||||||
|
19|export OPENCLAW_API_KEY="***"
|
||||||
|
20|```
|
||||||
|
21|
|
||||||
|
22|### Basic Usage
|
||||||
|
23|```python
|
||||||
|
24|from openclaw import AgentOrchestrator
|
||||||
|
25|
|
||||||
|
26|# Create an orchestrator
|
||||||
|
27|orchestrator = AgentOrchestrator()
|
||||||
|
28|
|
||||||
|
29|# Define agent roles
|
||||||
|
30|agents = {
|
||||||
|
31| "researcher": Agent(role="researcher"),
|
||||||
|
32| "analyst": Agent(role="analyst"),
|
||||||
|
33| "writer": Agent(role="writer")
|
||||||
|
34|}
|
||||||
|
35|
|
||||||
|
36|# Run a multi-agent workflow
|
||||||
|
37|result = orchestrator.run_task(
|
||||||
|
38| task="Write market analysis report",
|
||||||
|
39| agents=agents
|
||||||
|
40|)
|
||||||
|
41|```
|
||||||
|
42|
|
||||||
|
43|## Framework Components
|
||||||
|
44|
|
||||||
|
45|- **Agent Registry:** Pool of specialized agents
|
||||||
|
46|- **Task Dispatcher:** Routes tasks to appropriate agents
|
||||||
|
47|- **Collaboration Layer:** Enables agent-to-agent communication
|
||||||
|
48|- **Orchestration Engine:** Coordinates complex workflows
|
||||||
|
49|
|
||||||
|
50|## Use Cases
|
||||||
|
51|
|
||||||
|
52|- Market research automation
|
||||||
|
53|- Content generation pipelines
|
||||||
|
54|- Multi-step data analysis
|
||||||
|
55|- Autonomous decision making
|
||||||
|
56|
|
||||||
|
57|---
|
||||||
|
58|
|
||||||
|
59|*For advanced usage, refer to the Advanced Usage guide and API Reference documentation.*
|
||||||
@@ -0,0 +1,43 @@
|
|||||||
|
1|# 04 - Qwen3.5 Model Setup — Home
|
||||||
|
2|**Purpose:** Installation and configuration guides for Qwen3.5 model variants.
|
||||||
|
3|
|
||||||
|
4|## Available Models
|
||||||
|
5|
|
||||||
|
6|### **Qwen3.5-MoE (Mixture of Experts)** — Optimized for production inference with dynamic expert routing.
|
||||||
|
7|
|
||||||
|
8|### **Qwen3.5-Base** — Standard dense model variant.
|
||||||
|
9|
|
||||||
|
10|### **Qwen3.5-FineTuned** — Domain-specific fine-tuned variants.
|
||||||
|
11|
|
||||||
|
12|## GPU Compatibility
|
||||||
|
13|
|
||||||
|
14|- **AMD Strix Halo** — See [AMD GPU Passthrough Guide](../03\ -\ AMD\ GPU\ Passthrough/00\ -\ AMD\ GPU\ Passthrough.md)
|
||||||
|
15|- **NVIDIA RTX 4090** — Standard CUDA setup
|
||||||
|
16|- **Multi-GPU Clusters** — Distributed inference setup
|
||||||
|
17|
|
||||||
|
18|## Quick Start
|
||||||
|
19|
|
||||||
|
20|### Install Qwen3.5-MoE via Ollama
|
||||||
|
21|```bash
|
||||||
|
22|ollama pull qwen3.5:250b-moe
|
||||||
|
23|ollama serve
|
||||||
|
24|
|
||||||
|
25|# Run locally at 192.168.68.8:8080
|
||||||
|
26|ollama run qwen3.5:250b-moe "What are the top AI trends for 2026?"
|
||||||
|
27|```
|
||||||
|
28|
|
||||||
|
29|### Advanced Configuration
|
||||||
|
30|
|
||||||
|
31|For production deployments with dynamic expert selection:
|
||||||
|
32|- See `/60\ -\ Syslog/02\ -\ TECHNICAL\ INFRASTRUCTURE/04\ -\ Qwen3.5\ Model\ Setup/01\ -\ Qwen3.5-MoE\ Configuration.md`
|
||||||
|
33|- GPU passthrough: `/60\ -\ Syslog/02\ -\ TECHNICAL\ INFRASTRUCTURE/03\ -\ AMD\ GPU\ Passthrough/00\ -\ AMD\ GPU\ Passthrough.md`
|
||||||
|
34|
|
||||||
|
35|## Scripts
|
||||||
|
36|
|
||||||
|
37|- `vulkan-qwen35-moe-setup.sh` — Complete setup script for Qwen3.5-MoE with Vulkan backend
|
||||||
|
38|- `qwen35-moe-inference-config.sh` — Production inference configuration script
|
||||||
|
39|
|
||||||
|
40|---
|
||||||
|
41|
|
||||||
|
42|*For AMD GPU-specific setup, refer to the AMD GPU Passthrough guide.*
|
||||||
|
43|
|
||||||
@@ -0,0 +1,52 @@
|
|||||||
|
import smtplib
|
||||||
|
from email.message import EmailMessage
|
||||||
|
import os
|
||||||
|
import subprocess
|
||||||
|
|
||||||
|
msg = EmailMessage()
|
||||||
|
msg['Subject'] = 'Syslog Solution Logo - Design Brief & AI Concept'
|
||||||
|
msg['From'] = 'jerome@sysloggh.com'
|
||||||
|
msg['To'] = 'jtabiri@gmail.com'
|
||||||
|
|
||||||
|
body = """Hi [Designer Name],
|
||||||
|
|
||||||
|
I'm looking to have an AI-generated logo concept manually traced and finalized into a clean, flat, scalable vector format (SVG/EPS).
|
||||||
|
|
||||||
|
Company Name: Syslog Solution
|
||||||
|
Industry: Global Tech Consulting / Cloud Infrastructure
|
||||||
|
|
||||||
|
Attached is the AI-generated concept (gemini_heritage_1.png). I love the exact layout, structure, and blend of the Florida palm tree and the Ghanaian Sankofa bird. Because it's AI-generated, it needs a professional human touch to ensure the geometry is perfect, the lines are clean, and it works flawlessly as a corporate vector logo.
|
||||||
|
|
||||||
|
I have also attached the Design Brief (syslog-logo-brief.md) which includes the exact brand colors (Deep Slate Navy and Warm Orange) and our typography preferences.
|
||||||
|
|
||||||
|
Deliverables needed:
|
||||||
|
1. Master Vector Files (SVG, EPS, transparent PNG)
|
||||||
|
2. A few basic mockups using the final vector (e.g., business card, polo shirt embroidery, or 3D office sign)
|
||||||
|
|
||||||
|
Please let me know your turnaround time and rate for this vectorization and mockup project.
|
||||||
|
|
||||||
|
Thanks,
|
||||||
|
Jerome Tabiri
|
||||||
|
Syslog Solution LLC
|
||||||
|
"""
|
||||||
|
|
||||||
|
msg.set_content(body)
|
||||||
|
|
||||||
|
# Attach image
|
||||||
|
with open('/home/openclaw/.openclaw/workspace/syslog_logos/gemini_heritage_1.png', 'rb') as f:
|
||||||
|
msg.add_attachment(f.read(), maintype='image', subtype='png', filename='gemini_heritage_1.png')
|
||||||
|
|
||||||
|
# Attach brief
|
||||||
|
with open('/home/openclaw/.openclaw/workspace/syslog_logos/syslog-logo-brief.md', 'rb') as f:
|
||||||
|
msg.add_attachment(f.read(), maintype='text', subtype='markdown', filename='syslog-logo-brief.md')
|
||||||
|
|
||||||
|
# Send via msmtp
|
||||||
|
try:
|
||||||
|
p = subprocess.Popen(['msmtp', '-a', 'sysloggh', 'jtabiri@gmail.com'], stdin=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||||
|
out, err = p.communicate(msg.as_bytes())
|
||||||
|
if p.returncode == 0:
|
||||||
|
print("Email sent successfully!")
|
||||||
|
else:
|
||||||
|
print(f"Error sending email: {err.decode('utf-8')}")
|
||||||
|
except Exception as e:
|
||||||
|
print(f"Failed to execute msmtp: {e}")
|
||||||
@@ -0,0 +1,77 @@
|
|||||||
|
import os
|
||||||
|
|
||||||
|
svg_dir = "/home/openclaw/.openclaw/workspace/syslog_logos"
|
||||||
|
os.makedirs(svg_dir, exist_ok=True)
|
||||||
|
|
||||||
|
# Concept 1: The Spark (Abstract S)
|
||||||
|
svg_concept1 = """<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 500 500">
|
||||||
|
<rect width="500" height="500" fill="#0F172A"/>
|
||||||
|
<defs>
|
||||||
|
<linearGradient id="grad1" x1="0%" y1="0%" x2="100%" y2="100%">
|
||||||
|
<stop offset="0%" style="stop-color:#FB923C;stop-opacity:1" />
|
||||||
|
<stop offset="100%" style="stop-color:#EA580C;stop-opacity:1" />
|
||||||
|
</linearGradient>
|
||||||
|
</defs>
|
||||||
|
<!-- Abstract S made of two interlocking swooshes -->
|
||||||
|
<path d="M 250 150 C 350 150 350 250 250 250 C 150 250 150 350 250 350" fill="none" stroke="url(#grad1)" stroke-width="40" stroke-linecap="round"/>
|
||||||
|
<!-- Small tech dot -->
|
||||||
|
<circle cx="350" cy="150" r="20" fill="#FB923C"/>
|
||||||
|
<circle cx="150" cy="350" r="20" fill="#FB923C"/>
|
||||||
|
|
||||||
|
<text x="250" y="440" font-family="'Segoe UI', Roboto, sans-serif" font-size="32" font-weight="bold" fill="#F8FAFC" text-anchor="middle">SYSLOG SOLUTION</text>
|
||||||
|
<text x="250" y="470" font-family="'Segoe UI', Roboto, sans-serif" font-size="16" font-weight="normal" fill="#94A3B8" text-anchor="middle">YOUR FRIENDLY TECH ADVISOR</text>
|
||||||
|
</svg>"""
|
||||||
|
|
||||||
|
# Concept 2: The Tech Advisor (Cloud/Chat Hybrid)
|
||||||
|
svg_concept2 = """<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 500 500">
|
||||||
|
<rect width="500" height="500" fill="#FFFFFF"/>
|
||||||
|
<defs>
|
||||||
|
<linearGradient id="grad2" x1="0%" y1="0%" x2="100%" y2="100%">
|
||||||
|
<stop offset="0%" style="stop-color:#FB923C;stop-opacity:1" />
|
||||||
|
<stop offset="100%" style="stop-color:#EA580C;stop-opacity:1" />
|
||||||
|
</linearGradient>
|
||||||
|
</defs>
|
||||||
|
|
||||||
|
<!-- Cloud shape representing cloud tech -->
|
||||||
|
<path d="M 180 200 A 50 50 0 0 1 250 150 A 60 60 0 0 1 350 200 A 40 40 0 0 1 350 280 L 180 280 A 40 40 0 0 1 180 200 Z" fill="#0F172A"/>
|
||||||
|
|
||||||
|
<!-- Chat bubble representing the 'Advisor/Friendly' side, overlapping -->
|
||||||
|
<path d="M 150 230 C 150 190 200 160 250 160 C 300 160 350 190 350 230 C 350 270 300 300 250 300 C 230 300 210 295 195 285 L 140 305 L 155 260 C 150 250 150 240 150 230 Z" fill="url(#grad2)" opacity="0.9"/>
|
||||||
|
|
||||||
|
<!-- Simple nodes/connections inside the chat bubble -->
|
||||||
|
<circle cx="210" cy="230" r="8" fill="#FFFFFF"/>
|
||||||
|
<circle cx="250" cy="230" r="8" fill="#FFFFFF"/>
|
||||||
|
<circle cx="290" cy="230" r="8" fill="#FFFFFF"/>
|
||||||
|
|
||||||
|
<text x="250" y="380" font-family="'Segoe UI', Roboto, sans-serif" font-size="36" font-weight="bold" fill="#0F172A" text-anchor="middle">SYSLOG SOLUTION</text>
|
||||||
|
<text x="250" y="420" font-family="'Segoe UI', Roboto, sans-serif" font-size="18" font-weight="normal" fill="#FB923C" text-anchor="middle">WE MAKE TECH WORK FOR YOU</text>
|
||||||
|
</svg>"""
|
||||||
|
|
||||||
|
# Concept 3: The Connected Shield (Trust + Energy)
|
||||||
|
svg_concept3 = """<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 500 500">
|
||||||
|
<rect width="500" height="500" fill="#1E293B"/>
|
||||||
|
|
||||||
|
<!-- Shield Base -->
|
||||||
|
<path d="M 250 100 L 350 130 L 350 250 C 350 320 250 380 250 380 C 250 380 150 320 150 250 L 150 130 Z" fill="none" stroke="#FB923C" stroke-width="12" stroke-linejoin="round"/>
|
||||||
|
|
||||||
|
<!-- Central Node (Energy/Warmth) -->
|
||||||
|
<circle cx="250" cy="230" r="30" fill="#FB923C"/>
|
||||||
|
<!-- Connecting Lines to outer edges of shield -->
|
||||||
|
<line x1="250" y1="230" x2="250" y2="100" stroke="#FB923C" stroke-width="6" stroke-dasharray="4,4"/>
|
||||||
|
<line x1="250" y1="230" x2="350" y2="250" stroke="#FB923C" stroke-width="6" stroke-dasharray="4,4"/>
|
||||||
|
<line x1="250" y1="230" x2="150" y2="250" stroke="#FB923C" stroke-width="6" stroke-dasharray="4,4"/>
|
||||||
|
|
||||||
|
<text x="250" y="440" font-family="'Segoe UI', Roboto, sans-serif" font-size="32" font-weight="bold" fill="#FFFFFF" text-anchor="middle">SYSLOG SOLUTION</text>
|
||||||
|
<text x="250" y="470" font-family="'Segoe UI', Roboto, sans-serif" font-size="16" font-weight="normal" fill="#94A3B8" text-anchor="middle">TRUSTED TECH PARTNER</text>
|
||||||
|
</svg>"""
|
||||||
|
|
||||||
|
with open(f"{svg_dir}/concept_1_spark.svg", "w") as f:
|
||||||
|
f.write(svg_concept1)
|
||||||
|
|
||||||
|
with open(f"{svg_dir}/concept_2_advisor.svg", "w") as f:
|
||||||
|
f.write(svg_concept2)
|
||||||
|
|
||||||
|
with open(f"{svg_dir}/concept_3_shield.svg", "w") as f:
|
||||||
|
f.write(svg_concept3)
|
||||||
|
|
||||||
|
print(f"Generated SVGs in {svg_dir}")
|
||||||
@@ -1,119 +0,0 @@
|
|||||||
# 01 - Business Strategy
|
|
||||||
|
|
||||||
## 📊 Overview
|
|
||||||
This section contains the business strategy, market analysis, financial projections, and marketing materials for Syslog Solution LLC.
|
|
||||||
|
|
||||||
## 📁 Structure
|
|
||||||
|
|
||||||
```
|
|
||||||
01-business-strategy/
|
|
||||||
├── README.md # This file
|
|
||||||
├── business-vision/ # Company vision, mission, values
|
|
||||||
├── market-analysis/ # Market research, competition, positioning
|
|
||||||
├── financials/ # Financial projections, pricing, budgets
|
|
||||||
├── marketing/ # Pitch decks, brochures, marketing materials
|
|
||||||
└── legal/ # Business registration, contracts, compliance
|
|
||||||
```
|
|
||||||
|
|
||||||
## 🎯 Business Vision
|
|
||||||
|
|
||||||
### Mission Statement
|
|
||||||
To empower Ghanaian businesses with intelligent automation solutions that increase efficiency, reduce costs, and drive growth through AI and cloud technologies.
|
|
||||||
|
|
||||||
### Core Values
|
|
||||||
1. **Innovation** - Continuously exploring new technologies and approaches
|
|
||||||
2. **Reliability** - Building systems that work consistently and predictably
|
|
||||||
3. **Local Focus** - Understanding and addressing Ghana-specific business challenges
|
|
||||||
4. **Transparency** - Clear communication and honest business practices
|
|
||||||
5. **Excellence** - Delivering high-quality solutions that exceed expectations
|
|
||||||
|
|
||||||
### Target Markets
|
|
||||||
1. **Small & Medium Enterprises (SMEs)** in Ghana
|
|
||||||
2. **Tech Startups** needing scalable infrastructure
|
|
||||||
3. **Traditional Businesses** seeking digital transformation
|
|
||||||
4. **Government Agencies** requiring automation solutions
|
|
||||||
|
|
||||||
## 📈 Market Analysis
|
|
||||||
|
|
||||||
### Ghana Technology Landscape
|
|
||||||
- **Growing digital adoption** post-COVID
|
|
||||||
- **Increasing internet penetration** (mobile-first market)
|
|
||||||
- **Government initiatives** promoting digital transformation
|
|
||||||
- **Talent gap** in advanced technical skills
|
|
||||||
|
|
||||||
### Competitive Analysis
|
|
||||||
- **Local Competitors**: Few specialized AI/automation firms
|
|
||||||
- **International Competitors**: High-cost solutions not tailored for Ghana
|
|
||||||
- **Our Advantage**: Local understanding + technical expertise
|
|
||||||
|
|
||||||
### Market Opportunities
|
|
||||||
1. **AI Process Automation** - Reducing manual work in administrative tasks
|
|
||||||
2. **Cloud Migration** - Moving from on-premise to cloud infrastructure
|
|
||||||
3. **Business Intelligence** - Data-driven decision making
|
|
||||||
4. **Custom Software Development** - Tailored solutions for local needs
|
|
||||||
|
|
||||||
## 💰 Financial Strategy
|
|
||||||
|
|
||||||
### Revenue Streams
|
|
||||||
1. **Project-Based Consulting** - Custom solution development
|
|
||||||
2. **Managed Services** - Ongoing support and maintenance
|
|
||||||
3. **Product Licensing** - Reusable components and templates
|
|
||||||
4. **Training & Workshops** - Skills development programs
|
|
||||||
|
|
||||||
### Pricing Model
|
|
||||||
- **Hourly Rate**: $50-100/hour depending on complexity
|
|
||||||
- **Project-Based**: Fixed price for defined deliverables
|
|
||||||
- **Retainer Model**: Monthly fee for ongoing support
|
|
||||||
- **Product Licensing**: One-time or subscription fees
|
|
||||||
|
|
||||||
### Financial Projections
|
|
||||||
- **Year 1**: $50,000 - $100,000 revenue
|
|
||||||
- **Year 2**: $150,000 - $250,000 revenue
|
|
||||||
- **Year 3**: $300,000 - $500,000 revenue
|
|
||||||
- **Profit Margin Target**: 30-40%
|
|
||||||
|
|
||||||
## 🚀 Growth Strategy
|
|
||||||
|
|
||||||
### Short-Term (0-6 months)
|
|
||||||
1. Complete 3-5 pilot projects
|
|
||||||
2. Build portfolio and case studies
|
|
||||||
3. Establish partnerships with local businesses
|
|
||||||
4. Develop reusable templates and components
|
|
||||||
|
|
||||||
### Medium-Term (6-18 months)
|
|
||||||
1. Expand team to 5-7 members
|
|
||||||
2. Develop proprietary AI automation platform
|
|
||||||
3. Establish recurring revenue streams
|
|
||||||
4. Expand to other West African markets
|
|
||||||
|
|
||||||
### Long-Term (18-36 months)
|
|
||||||
1. Become leading AI automation provider in Ghana
|
|
||||||
2. Launch SaaS products for specific industries
|
|
||||||
3. Establish training academy for AI skills
|
|
||||||
4. Expand to 10+ African countries
|
|
||||||
|
|
||||||
## 📋 Key Documents
|
|
||||||
|
|
||||||
### Required Documents
|
|
||||||
- [ ] Business Plan (complete version)
|
|
||||||
- [ ] Pitch Deck for investors
|
|
||||||
- [ ] Marketing Brochure
|
|
||||||
- [ ] Client Proposal Template
|
|
||||||
- [ ] Service Level Agreement (SLA) Template
|
|
||||||
- [ ] Non-Disclosure Agreement (NDA) Template
|
|
||||||
|
|
||||||
### Status Tracking
|
|
||||||
- **Last Updated**: April 2026
|
|
||||||
- **Next Review**: July 2026
|
|
||||||
- **Owner**: Jerome Tabiri
|
|
||||||
- **Version**: 1.0
|
|
||||||
|
|
||||||
## 🔗 Related Sections
|
|
||||||
- **Technical Architecture** → How we implement solutions
|
|
||||||
- **Operations** → How we deliver and support
|
|
||||||
- **Customer Portal** → How clients interact with us
|
|
||||||
- **Development** → How we build and maintain solutions
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
*This documentation is proprietary to Syslog Solution LLC. Unauthorized distribution prohibited.*
|
|
||||||
@@ -1,58 +0,0 @@
|
|||||||
1|# 01 - BUSINESS & STRATEGY — Home
|
|
||||||
2|**Purpose:** Business strategy, market analysis, and growth planning for Syslog GH/LLC.
|
|
||||||
3|
|
|
||||||
4|## Core Areas
|
|
||||||
5|
|
|
||||||
6|### **Customer Acquisition**
|
|
||||||
7|- SMB-focused AI consulting (Discovery-first approach)
|
|
||||||
8|- Tech Edge Partnerships (AWS, GitHub, Cloudflare)
|
|
||||||
9|- Ghana market entry strategy
|
|
||||||
10|- LinkedIn organic growth campaigns
|
|
||||||
11|
|
|
||||||
12|### **Service Lines**
|
|
||||||
13|- $299/mo AI Navigation Partner
|
|
||||||
14|- $399/mo AI Agent Deployment
|
|
||||||
15|- $1.5-5K Custom Implementation Projects
|
|
||||||
16|- 70-80% recurring revenue target
|
|
||||||
17|
|
|
||||||
18|### **Strategic Differentiators**
|
|
||||||
19|- Privacy-focused AI (local deployment, minimal data collection)
|
|
||||||
20|- OpenMAIC education framework
|
|
||||||
21|- Brother co-founders (Jerome & Theodore) for dual expertise
|
|
||||||
22|- Open-source community positioning
|
|
||||||
23|
|
|
||||||
24|### **Target Markets**
|
|
||||||
25|1. **Ghana:** AI adoption gap (65% SMB adoption, 87% data concerns)
|
|
||||||
26|2. **US:** Discovery-first AI services ($2.5B addressable market)
|
|
||||||
27|3. **Remote:** Distributed workforce support
|
|
||||||
28|
|
|
||||||
29|### **Competitive Landscape**
|
|
||||||
30|- **Traditional IT Firms:** Lack AI expertise; high cost
|
|
||||||
31|- **Pure Play AI Agencies:** Overkill pricing ($10K+), no privacy focus
|
|
||||||
32|- **DIY Consultants:** Inconsistent quality, no framework
|
|
||||||
33|- **Syslog Position:** Balanced, affordable, privacy-focused
|
|
||||||
34|
|
|
||||||
35|### **Key Performance Metrics**
|
|
||||||
36|- **Pipeline:** 12 SMB leads Q3 2026
|
|
||||||
37|- **Conversion:** 30% target (vs. 20% industry average)
|
|
||||||
38|- **Average Deal Size:** $1,250 (navigation) → $3,750 (implementation)
|
|
||||||
39|- **CAC Target:** $350 (vs. $1,500 industry average)
|
|
||||||
40|- **LTV Target:** $7,500
|
|
||||||
41|- **Payback Period:** <6 months
|
|
||||||
42|
|
|
||||||
43|### **Strategic Initiatives**
|
|
||||||
44|- OpenMAIC education program (Q4 2026 launch)
|
|
||||||
45|- Tech Edge partnership formalization (Q3 2026)
|
|
||||||
46|- Remote-first infrastructure deployment (AWS, Docker)
|
|
||||||
47|- Knowledge sharing culture (internal wikis, agent frameworks)
|
|
||||||
48|
|
|
||||||
49|### **Risk Factors & Mitigations**
|
|
||||||
50|- **Customer churn:** 15% target → 20% max; mitigate with ROI tracking
|
|
||||||
51|- **Lead quality:** 40% low-quality leads → improve qualification criteria
|
|
||||||
52|- **Pricing pressure:** Position on value/ROI, not cost
|
|
||||||
53|- **Competition:** Early mover in SMB segment, build community moat
|
|
||||||
54|
|
|
||||||
55|---
|
|
||||||
56|
|
|
||||||
57|*This section is the foundation of Syslog GH/LLC strategy. Review before client calls and quarterly planning sessions.*
|
|
||||||
58|
|
|
||||||
@@ -1,223 +0,0 @@
|
|||||||
# 02 - Technical Architecture
|
|
||||||
|
|
||||||
## 🏗️ Overview
|
|
||||||
This section contains the technical architecture, infrastructure design, deployment standards, and technical documentation for Syslog Solution LLC.
|
|
||||||
|
|
||||||
## 📁 Structure
|
|
||||||
|
|
||||||
```
|
|
||||||
02-technical-architecture/
|
|
||||||
├── README.md # This file
|
|
||||||
├── infrastructure-overview/ # High-level architecture diagrams
|
|
||||||
├── aws-architecture/ # AWS-specific designs and patterns
|
|
||||||
├── proxmox-cluster/ # Homelab infrastructure documentation
|
|
||||||
├── ai-agents-framework/ # AI agent design and implementation
|
|
||||||
├── deployment-standards/ # Deployment procedures and best practices
|
|
||||||
├── security-compliance/ # Security policies and compliance
|
|
||||||
└── monitoring-logging/ # Monitoring, alerting, and logging
|
|
||||||
```
|
|
||||||
|
|
||||||
## 🎯 Architecture Principles
|
|
||||||
|
|
||||||
### Core Principles
|
|
||||||
1. **Automation First** - Everything that can be automated should be automated
|
|
||||||
2. **Infrastructure as Code** - All infrastructure defined in version-controlled code
|
|
||||||
3. **Security by Design** - Security integrated from the beginning, not as an afterthought
|
|
||||||
4. **Scalability** - Systems designed to scale with business growth
|
|
||||||
5. **Cost Optimization** - Efficient use of resources without compromising quality
|
|
||||||
6. **Disaster Recovery** - Built-in redundancy and recovery capabilities
|
|
||||||
|
|
||||||
### Technology Stack
|
|
||||||
|
|
||||||
#### Cloud Infrastructure
|
|
||||||
- **Primary Cloud**: AWS (Amazon Web Services)
|
|
||||||
- **Secondary Cloud**: Proxmox Homelab (for development/testing)
|
|
||||||
- **Container Orchestration**: Docker, Docker Compose
|
|
||||||
- **Infrastructure as Code**: Terraform, Ansible
|
|
||||||
|
|
||||||
#### AI & Automation
|
|
||||||
- **AI Frameworks**: LangChain, LlamaIndex, AutoGen
|
|
||||||
- **Model Providers**: AWS Bedrock, OpenAI, Anthropic, Local models
|
|
||||||
- **Orchestration**: Hermes Agent, Custom multi-agent systems
|
|
||||||
- **Vector Databases**: Pinecone, Chroma, FAISS
|
|
||||||
|
|
||||||
#### Development & Deployment
|
|
||||||
- **Programming Languages**: Python, JavaScript/TypeScript, Bash
|
|
||||||
- **Web Frameworks**: FastAPI, React, Next.js
|
|
||||||
- **CI/CD**: GitHub Actions, AWS CodePipeline
|
|
||||||
- **Monitoring**: Prometheus, Grafana, CloudWatch
|
|
||||||
|
|
||||||
## 🏢 Infrastructure Overview
|
|
||||||
|
|
||||||
### AWS Organization Structure
|
|
||||||
```
|
|
||||||
AWS Organization (Root)
|
|
||||||
├── Management OU
|
|
||||||
│ ├── Management Account (Tier 0)
|
|
||||||
│ └── IAM Identity Center
|
|
||||||
├── Security OU
|
|
||||||
│ ├── Security Account (Tier 0)
|
|
||||||
│ └── Log Archive Account
|
|
||||||
├── Workloads OU
|
|
||||||
│ ├── Development Account (Tier 1)
|
|
||||||
│ ├── Staging Account (Tier 1)
|
|
||||||
│ └── Production Account (Tier 1)
|
|
||||||
└── Sandbox OU
|
|
||||||
└── Sandbox Account (Tier 2)
|
|
||||||
```
|
|
||||||
|
|
||||||
### Proxmox Homelab
|
|
||||||
- **Primary Node**: hwpve (HP Z640)
|
|
||||||
- **Secondary Node**: acerpve (Acer workstation)
|
|
||||||
- **Tertiary Node**: minipve (Mini PC)
|
|
||||||
- **Storage**: PBS (Proxmox Backup Server)
|
|
||||||
- **Purpose**: Development, testing, proof-of-concepts
|
|
||||||
|
|
||||||
### Network Architecture
|
|
||||||
- **VPC Design**: Multi-AZ, public/private subnets
|
|
||||||
- **Security Groups**: Least privilege access
|
|
||||||
- **Network ACLs**: Additional layer of security
|
|
||||||
- **VPN/Connectivity**: Site-to-site VPN for hybrid cloud
|
|
||||||
|
|
||||||
## 🤖 AI Agents Framework
|
|
||||||
|
|
||||||
### Multi-Agent System Architecture
|
|
||||||
```
|
|
||||||
┌─────────────────┐
|
|
||||||
│ Orchestrator │
|
|
||||||
│ (Hermes) │
|
|
||||||
└────────┬────────┘
|
|
||||||
│
|
|
||||||
┌────────┴────────┐
|
|
||||||
│ Specialized │
|
|
||||||
│ Agents │
|
|
||||||
├─────────────────┤
|
|
||||||
│ • Research Agent│
|
|
||||||
│ • Coding Agent │
|
|
||||||
│ • Data Agent │
|
|
||||||
│ • QA Agent │
|
|
||||||
│ • Deploy Agent │
|
|
||||||
└─────────────────┘
|
|
||||||
```
|
|
||||||
|
|
||||||
### Agent Capabilities
|
|
||||||
1. **Research Agent** - Market research, competitor analysis
|
|
||||||
2. **Coding Agent** - Software development, code review
|
|
||||||
3. **Data Agent** - Data analysis, visualization, ETL
|
|
||||||
4. **QA Agent** - Testing, validation, quality assurance
|
|
||||||
5. **Deploy Agent** - Deployment, monitoring, maintenance
|
|
||||||
|
|
||||||
### RAG (Retrieval Augmented Generation)
|
|
||||||
- **Document Indexing**: Company knowledge base, client documentation
|
|
||||||
- **Vector Storage**: Pinecone for production, Chroma for development
|
|
||||||
- **Retrieval**: Semantic search with hybrid search (keyword + vector)
|
|
||||||
- **Generation**: Context-aware responses using LLMs
|
|
||||||
|
|
||||||
## 🚀 Deployment Standards
|
|
||||||
|
|
||||||
### Development Workflow
|
|
||||||
1. **Local Development** → Docker Compose for local testing
|
|
||||||
2. **Code Review** → GitHub Pull Requests with automated checks
|
|
||||||
3. **Staging Deployment** → Automated deployment to staging environment
|
|
||||||
4. **Testing** → Automated tests + manual validation
|
|
||||||
5. **Production Deployment** → Blue-green deployment with rollback
|
|
||||||
|
|
||||||
### Infrastructure Deployment
|
|
||||||
```bash
|
|
||||||
# 1. Initialize Terraform
|
|
||||||
terraform init
|
|
||||||
|
|
||||||
# 2. Plan changes
|
|
||||||
terraform plan -out=tfplan
|
|
||||||
|
|
||||||
# 3. Apply changes (after approval)
|
|
||||||
terraform apply tfplan
|
|
||||||
|
|
||||||
# 4. Verify deployment
|
|
||||||
./scripts/verify-deployment.sh
|
|
||||||
```
|
|
||||||
|
|
||||||
### Application Deployment
|
|
||||||
```bash
|
|
||||||
# 1. Build container
|
|
||||||
docker build -t app:latest .
|
|
||||||
|
|
||||||
# 2. Push to registry
|
|
||||||
docker push registry.sysloggh.com/app:latest
|
|
||||||
|
|
||||||
# 3. Deploy to Kubernetes/ECS
|
|
||||||
./scripts/deploy-app.sh
|
|
||||||
```
|
|
||||||
|
|
||||||
## 🔒 Security & Compliance
|
|
||||||
|
|
||||||
### Security Controls
|
|
||||||
1. **Identity & Access Management**
|
|
||||||
- IAM users with MFA requirement
|
|
||||||
- Role-based access control (RBAC)
|
|
||||||
- Least privilege principle
|
|
||||||
- Regular access reviews
|
|
||||||
|
|
||||||
2. **Data Protection**
|
|
||||||
- Encryption at rest and in transit
|
|
||||||
- Secure key management (AWS KMS)
|
|
||||||
- Data classification and handling
|
|
||||||
- Backup and recovery procedures
|
|
||||||
|
|
||||||
3. **Network Security**
|
|
||||||
- VPC with security groups and NACLs
|
|
||||||
- Web Application Firewall (WAF)
|
|
||||||
- DDoS protection
|
|
||||||
- VPN for secure access
|
|
||||||
|
|
||||||
### Compliance Framework
|
|
||||||
- **GDPR** - Data protection for EU citizens
|
|
||||||
- **ISO 27001** - Information security management
|
|
||||||
- **SOC 2** - Security, availability, processing integrity
|
|
||||||
- **Local Regulations** - Ghana data protection laws
|
|
||||||
|
|
||||||
## 📊 Monitoring & Observability
|
|
||||||
|
|
||||||
### Monitoring Stack
|
|
||||||
- **Infrastructure Monitoring**: CloudWatch, Prometheus
|
|
||||||
- **Application Monitoring**: Application Insights, OpenTelemetry
|
|
||||||
- **Log Management**: CloudWatch Logs, ELK Stack
|
|
||||||
- **Alerting**: SNS, PagerDuty, Telegram bots
|
|
||||||
|
|
||||||
### Key Metrics
|
|
||||||
1. **Availability** - Uptime percentage, error rates
|
|
||||||
2. **Performance** - Response times, throughput
|
|
||||||
3. **Cost** - Cloud spend, cost optimization opportunities
|
|
||||||
4. **Security** - Vulnerability scans, compliance status
|
|
||||||
|
|
||||||
### Incident Response
|
|
||||||
1. **Detection** - Automated alerts trigger incident
|
|
||||||
2. **Response** - Designated team member investigates
|
|
||||||
3. **Resolution** - Fix applied and verified
|
|
||||||
4. **Post-Mortem** - Root cause analysis and prevention
|
|
||||||
|
|
||||||
## 📋 Key Documents
|
|
||||||
|
|
||||||
### Required Documents
|
|
||||||
- [ ] Infrastructure Architecture Diagrams
|
|
||||||
- [ ] Deployment Runbooks
|
|
||||||
- [ ] Security Policy Document
|
|
||||||
- [ ] Disaster Recovery Plan
|
|
||||||
- [ ] Capacity Planning Guide
|
|
||||||
- [ ] Cost Optimization Strategy
|
|
||||||
|
|
||||||
### Status Tracking
|
|
||||||
- **Last Updated**: April 2026
|
|
||||||
- **Next Review**: May 2026
|
|
||||||
- **Owner**: Jerome Tabiri
|
|
||||||
- **Version**: 1.0
|
|
||||||
|
|
||||||
## 🔗 Related Sections
|
|
||||||
- **Business Strategy** → Why we build these systems
|
|
||||||
- **Operations** → How we maintain and support
|
|
||||||
- **Customer Portal** → Client-facing technical documentation
|
|
||||||
- **Development** → Implementation details and coding standards
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
*This documentation is proprietary to Syslog Solution LLC. Unauthorized distribution prohibited.*
|
|
||||||
-70
@@ -1,70 +0,0 @@
|
|||||||
1|# 04 - Autonomous AI Agents — Home
|
|
||||||
2|**Purpose:** Research and implementation of autonomous agent workflows.
|
|
||||||
3|
|
|
||||||
4|## Overview
|
|
||||||
5|
|
|
||||||
6|Autonomous AI agents can execute multi-step tasks independently, learn from experience, and make decisions based on context. This section covers advanced orchestration patterns for production-grade agent systems.
|
|
||||||
7|
|
|
||||||
8|## Key Capabilities
|
|
||||||
9|
|
|
||||||
10|### **Multi-Agent Collaboration**
|
|
||||||
11|- Role-based agent delegation
|
|
||||||
12|- Cross-agent memory sharing
|
|
||||||
13|- Conflict resolution protocols
|
|
||||||
14|- Distributed task execution
|
|
||||||
15|
|
|
||||||
16|### **Autonomous Behaviors**
|
|
||||||
17|- Self-correction loops
|
|
||||||
18|- Error recovery mechanisms
|
|
||||||
19|- Performance optimization
|
|
||||||
20|- Adaptive resource allocation
|
|
||||||
21|
|
|
||||||
22|### **Advanced Patterns**
|
|
||||||
23|- Agent swarms (10+ coordinated agents)
|
|
||||||
24|- Continuous learning cycles
|
|
||||||
25|- Human-in-the-loop intervention points
|
|
||||||
26|- Audit trails and observability
|
|
||||||
27|
|
|
||||||
28|## Implementation Strategies
|
|
||||||
29|
|
|
||||||
30|### **Sequential Workflows**
|
|
||||||
31|```python
|
|
||||||
32|agent1.run(task="Research market")
|
|
||||||
33|agent2.run(task="Analyze data")
|
|
||||||
34|agent3.run(task="Generate report")
|
|
||||||
35|```
|
|
||||||
36|
|
|
||||||
37|### **Parallel Workflows**
|
|
||||||
38|```python
|
|
||||||
39|results = await asyncio.gather(
|
|
||||||
40| agent1.run(task="A"),
|
|
||||||
41| agent2.run(task="B"),
|
|
||||||
42| agent3.run(task="C")
|
|
||||||
43|)
|
|
||||||
44|```
|
|
||||||
45|
|
|
||||||
46|### **Feedback Loops**
|
|
||||||
47|```python
|
|
||||||
48|while not agent.is_satisfied(result):
|
|
||||||
49| agent.improve(result)
|
|
||||||
50| result = agent.execute(prompt)
|
|
||||||
51|```
|
|
||||||
52|
|
|
||||||
53|## Use Cases
|
|
||||||
54|
|
|
||||||
55|- Market research automation
|
|
||||||
56|- Multi-step data analysis pipelines
|
|
||||||
57|- Customer support orchestration
|
|
||||||
58|- Content generation workflows
|
|
||||||
59|- Codebase refactoring agents
|
|
||||||
60|
|
|
||||||
61|## Related Frameworks
|
|
||||||
62|
|
|
||||||
63|- **[OpenClaw](../02\ -\ OpenClaw\ Framework/)** — Agent orchestration platform
|
|
||||||
64|- **[MCP](../03\ -\ MCP\ \(Model\ Context\ Protocol\)/)** — Tool integration layer
|
|
||||||
65|- **[OpenMAIC](../06\ -\ OpenMAIC\ Education/)** — Educational resources
|
|
||||||
66|
|
|
||||||
67|---
|
|
||||||
68|
|
|
||||||
69|*Advanced agent patterns for Jerome & Theodore's complex automation projects.*
|
|
||||||
70|
|
|
||||||
-53
@@ -1,53 +0,0 @@
|
|||||||
1|# 01 - Claude Code & Opencode — Home
|
|
||||||
2|**Purpose:** Agent framework tutorials and best practices for Claude Code and OpenCode CLI.
|
|
||||||
3|
|
|
||||||
4|## Overview
|
|
||||||
5|
|
|
||||||
6|This section provides practical guides for deploying and managing AI coding agents using Claude Code and OpenCode CLI tools.
|
|
||||||
7|
|
|
||||||
8|## Contents
|
|
||||||
9|
|
|
||||||
10|### **Claude Code**
|
|
||||||
11|- Quick start and configuration
|
|
||||||
12|- Integration with IDEs
|
|
||||||
13|- Custom agent definitions
|
|
||||||
14|- Security best practices
|
|
||||||
15|
|
|
||||||
16|### **OpenCode**
|
|
||||||
17|- CLI setup and usage
|
|
||||||
18|- Extending with custom commands
|
|
||||||
19|- Multi-agent orchestration
|
|
||||||
20|- Production deployment patterns
|
|
||||||
21|
|
|
||||||
22|### **Best Practices**
|
|
||||||
23|- Context window management
|
|
||||||
24|- Agent sandboxing rules
|
|
||||||
25|- Error handling patterns
|
|
||||||
26|- Performance optimization
|
|
||||||
27|
|
|
||||||
28|## Quick Start
|
|
||||||
29|
|
|
||||||
30|```bash
|
|
||||||
31|# Install OpenCode CLI
|
|
||||||
32|pip install opencode-cli
|
|
||||||
33|
|
|
||||||
34|# Configure API keys
|
|
||||||
35|export OPENAI_API_KEY="***"
|
|
||||||
36|
|
|
||||||
37|# Run Claude Code
|
|
||||||
38|opencode run "Analyze this codebase for security issues"
|
|
||||||
39|
|
|
||||||
40|# Create custom agent
|
|
||||||
41|opencode agent create --name my-helper --template best-practices
|
|
||||||
42|```
|
|
||||||
43|
|
|
||||||
44|## Related Frameworks
|
|
||||||
45|
|
|
||||||
46|- **[MCP (Model Context Protocol)](../03\ -\ MCP\ \(Model\ Context\ Protocol\)/)** — Tool integration
|
|
||||||
47|- **[OpenClaw Framework](../02\ -\ OpenClaw\ Framework/)** — Multi-agent orchestration
|
|
||||||
48|- **[Autonomous AI Agents](../04\ -\ Autonomous\ AI\ Agents/)** — Advanced workflows
|
|
||||||
49|
|
|
||||||
50|---
|
|
||||||
51|
|
|
||||||
52|*Practical guides for Jerome & Theodore to implement AI coding agents in their daily workflow.*
|
|
||||||
53|
|
|
||||||
@@ -1,87 +0,0 @@
|
|||||||
1|# 02 - MCP (Model Context Protocol) — Home
|
|
||||||
2|**Purpose:** MCP integration guides and implementation examples.
|
|
||||||
3|
|
|
||||||
4|## What is MCP?
|
|
||||||
5|Model Context Protocol (MCP) is a standardized interface for connecting LLMs to external tools, data sources, and services.
|
|
||||||
6|
|
|
||||||
7|## MCP Benefits
|
|
||||||
8|- **Unified interface** for tool integration
|
|
||||||
9|- **Hot-swappable** tool providers
|
|
||||||
10|- **Standardized** input/output schemas
|
|
||||||
11|- **Type-safe** API definitions
|
|
||||||
12|
|
|
||||||
13|## Core Concepts
|
|
||||||
14|
|
|
||||||
15|### Tools
|
|
||||||
16|External capabilities exposed to the model:
|
|
||||||
17|- File system access
|
|
||||||
18|- Database queries
|
|
||||||
19|- API endpoints
|
|
||||||
20|- Custom business logic
|
|
||||||
21|
|
|
||||||
22|### Resources
|
|
||||||
23|Data sources the model can read:
|
|
||||||
24|- Documents
|
|
||||||
25|- Configuration files
|
|
||||||
26|- Real-time data feeds
|
|
||||||
27|- Knowledge bases
|
|
||||||
28|
|
|
||||||
29|### Prompts
|
|
||||||
30|Pre-defined interaction templates:
|
|
||||||
31|- Task initiation patterns
|
|
||||||
32|- System prompt variations
|
|
||||||
33|- Role-definition templates
|
|
||||||
34|
|
|
||||||
35|## Quick Start
|
|
||||||
36|
|
|
||||||
37|```bash
|
|
||||||
38|# Install MCP server
|
|
||||||
39|pip install mcp-server-filesystem mcp-server-sqlite
|
|
||||||
40|
|
|
||||||
41|# Start a filesystem MCP server
|
|
||||||
42|mcp-server-filesystem --path /path/to/allowed/directory
|
|
||||||
43|
|
|
||||||
44|# Connect via client
|
|
||||||
45|from mcp import ClientSession, StdioServerParameters
|
|
||||||
46|
|
|
||||||
47|async with ClientSession(
|
|
||||||
48| stdio_server_parameters=StdioServerParameters(
|
|
||||||
49| command="mcp-server-filesystem",
|
|
||||||
50| args=["--path", "/path/to/allowed/directory"]
|
|
||||||
51| )
|
|
||||||
52|) as session:
|
|
||||||
53| # List available tools
|
|
||||||
54| tools = await session.list_tools()
|
|
||||||
55|```
|
|
||||||
56|
|
|
||||||
57|## Available MCP Servers
|
|
||||||
58|
|
|
||||||
59|- **Filesystem:** Access documents and configuration files
|
|
||||||
60|- **SQL databases:** Query relational databases safely
|
|
||||||
61|- **API Gateway:** Connect to REST/GraphQL endpoints
|
|
||||||
62|- **Custom Business Logic:** Integrate internal tools and services
|
|
||||||
63|
|
|
||||||
64|## Security Considerations
|
|
||||||
65|
|
|
||||||
66|- **Path whitelisting:** Only allow specific directories
|
|
||||||
67|- **Query rate limiting:** Prevent resource exhaustion
|
|
||||||
68|- **Input sanitization:** Validate all user inputs
|
|
||||||
69|- **Token-based access:** Require authentication for sensitive operations
|
|
||||||
70|
|
|
||||||
71|## Use Cases
|
|
||||||
72|
|
|
||||||
73|- **Document analysis:** Read and process large document collections
|
|
||||||
74|- **Database queries:** Extract insights from operational databases
|
|
||||||
75|- **API orchestration:** Coordinate across multiple external services
|
|
||||||
76|- **Code generation:** Write and execute code safely
|
|
||||||
77|
|
|
||||||
78|## References
|
|
||||||
79|
|
|
||||||
80|- [MCP Specification](https://modelcontextprotocol.io)
|
|
||||||
81|- [MCP Server Implementations](https://github.com/modelcontextprotocol/servers)
|
|
||||||
82|- [Integration Examples](../03%20-%20AI%20AGENTS%20&%20LEARNING/02%20-%20OpenClaw%20Framework/)
|
|
||||||
83|
|
|
||||||
84|---
|
|
||||||
85|
|
|
||||||
86|*MCP integrates seamlessly with OpenClaw agent orchestration for scalable AI applications.*
|
|
||||||
87|
|
|
||||||
-59
@@ -1,59 +0,0 @@
|
|||||||
1|# OpenClaw Framework — Home
|
|
||||||
2|**Purpose:** Complete guide to setting up and using the OpenClaw agent orchestration framework.
|
|
||||||
3|
|
|
||||||
4|## What is OpenClaw?
|
|
||||||
5|OpenClaw provides a powerful framework for orchestrating AI agents, enabling multi-agent collaboration, task delegation, and complex workflow automation.
|
|
||||||
6|
|
|
||||||
7|## Quick Start
|
|
||||||
8|
|
|
||||||
9|### Installation
|
|
||||||
10|```bash
|
|
||||||
11|# Clone the repository
|
|
||||||
12|git clone https://github.com/openclaw/openclaw.git
|
|
||||||
13|cd openclaw
|
|
||||||
14|
|
|
||||||
15|# Install dependencies
|
|
||||||
16|pip install -r requirements.txt
|
|
||||||
17|
|
|
||||||
18|# Configure API keys
|
|
||||||
19|export OPENCLAW_API_KEY="***"
|
|
||||||
20|```
|
|
||||||
21|
|
|
||||||
22|### Basic Usage
|
|
||||||
23|```python
|
|
||||||
24|from openclaw import AgentOrchestrator
|
|
||||||
25|
|
|
||||||
26|# Create an orchestrator
|
|
||||||
27|orchestrator = AgentOrchestrator()
|
|
||||||
28|
|
|
||||||
29|# Define agent roles
|
|
||||||
30|agents = {
|
|
||||||
31| "researcher": Agent(role="researcher"),
|
|
||||||
32| "analyst": Agent(role="analyst"),
|
|
||||||
33| "writer": Agent(role="writer")
|
|
||||||
34|}
|
|
||||||
35|
|
|
||||||
36|# Run a multi-agent workflow
|
|
||||||
37|result = orchestrator.run_task(
|
|
||||||
38| task="Write market analysis report",
|
|
||||||
39| agents=agents
|
|
||||||
40|)
|
|
||||||
41|```
|
|
||||||
42|
|
|
||||||
43|## Framework Components
|
|
||||||
44|
|
|
||||||
45|- **Agent Registry:** Pool of specialized agents
|
|
||||||
46|- **Task Dispatcher:** Routes tasks to appropriate agents
|
|
||||||
47|- **Collaboration Layer:** Enables agent-to-agent communication
|
|
||||||
48|- **Orchestration Engine:** Coordinates complex workflows
|
|
||||||
49|
|
|
||||||
50|## Use Cases
|
|
||||||
51|
|
|
||||||
52|- Market research automation
|
|
||||||
53|- Content generation pipelines
|
|
||||||
54|- Multi-step data analysis
|
|
||||||
55|- Autonomous decision making
|
|
||||||
56|
|
|
||||||
57|---
|
|
||||||
58|
|
|
||||||
59|*For advanced usage, refer to the Advanced Usage guide and API Reference documentation.*
|
|
||||||
+92
-92
@@ -1,92 +1,92 @@
|
|||||||
1|# 06 - OpenMAIC Education — Home
|
1|# 06 - OpenMAIC Education — Home
|
||||||
2|**Purpose:** OpenMAIC (Open Multi-Agent AI Collaboration) educational resources and curriculum.
|
2|**Purpose:** OpenMAIC (Open Multi-Agent AI Collaboration) educational resources and curriculum.
|
||||||
3|
|
3|
|
||||||
4|## What is OpenMAIC?
|
4|## What is OpenMAIC?
|
||||||
5|
|
5|
|
||||||
6|OpenMAIC (Open Multi-Agent AI Collaboration) is an educational framework designed to help teams understand and implement multi-agent AI systems. It provides:
|
6|OpenMAIC (Open Multi-Agent AI Collaboration) is an educational framework designed to help teams understand and implement multi-agent AI systems. It provides:
|
||||||
7|
|
7|
|
||||||
8|- **Structured Curriculum:** From fundamentals to advanced patterns
|
8|- **Structured Curriculum:** From fundamentals to advanced patterns
|
||||||
9|- **Hands-on Exercises:** Real-world practice through coding challenges
|
9|- **Hands-on Exercises:** Real-world practice through coding challenges
|
||||||
10|- **Community Learning:** Collaborative problem-solving and knowledge sharing
|
10|- **Community Learning:** Collaborative problem-solving and knowledge sharing
|
||||||
11|
|
11|
|
||||||
12|## Curriculum Structure
|
12|## Curriculum Structure
|
||||||
13|
|
13|
|
||||||
14|### **Module 1: Fundamentals**
|
14|### **Module 1: Fundamentals**
|
||||||
15|- Introduction to multi-agent systems
|
15|- Introduction to multi-agent systems
|
||||||
16|- Agent role definition and capabilities
|
16|- Agent role definition and capabilities
|
||||||
17|- Basic orchestration patterns
|
17|- Basic orchestration patterns
|
||||||
18|- Simple agent collaboration examples
|
18|- Simple agent collaboration examples
|
||||||
19|
|
19|
|
||||||
20|### **Module 2: Advanced Collaboration**
|
20|### **Module 2: Advanced Collaboration**
|
||||||
21|- Complex workflow design
|
21|- Complex workflow design
|
||||||
22|- Context sharing between agents
|
22|- Context sharing between agents
|
||||||
23|- Error handling and recovery
|
23|- Error handling and recovery
|
||||||
24|- Performance optimization
|
24|- Performance optimization
|
||||||
25|
|
25|
|
||||||
26|### **Module 3: Production Patterns**
|
26|### **Module 3: Production Patterns**
|
||||||
27|- Scaling to 10+ agents
|
27|- Scaling to 10+ agents
|
||||||
28|- Monitoring and diagnostics
|
28|- Monitoring and diagnostics
|
||||||
29|- Security best practices
|
29|- Security best practices
|
||||||
30|- Cost optimization strategies
|
30|- Cost optimization strategies
|
||||||
31|
|
31|
|
||||||
32|### **Module 4: Real-World Applications**
|
32|### **Module 4: Real-World Applications**
|
||||||
33|- Market analysis automation
|
33|- Market analysis automation
|
||||||
34|- Customer support orchestration
|
34|- Customer support orchestration
|
||||||
35|- Content pipeline automation
|
35|- Content pipeline automation
|
||||||
36|- Data processing workflows
|
36|- Data processing workflows
|
||||||
37|
|
37|
|
||||||
38|## Getting Started
|
38|## Getting Started
|
||||||
39|
|
39|
|
||||||
40|```bash
|
40|```bash
|
||||||
41|# Step 1: Install OpenMAIC
|
41|# Step 1: Install OpenMAIC
|
||||||
42|pip install openmaic-core openmaic-visualizer
|
42|pip install openmaic-core openmaic-visualizer
|
||||||
43|
|
43|
|
||||||
44|# Step 2: Clone learning resources
|
44|# Step 2: Clone learning resources
|
||||||
45|git clone https://github.com/sysloggh/openmaic-learning.git
|
45|git clone https://github.com/sysloggh/openmaic-learning.git
|
||||||
46|cd openmaic-learning/modules
|
46|cd openmaic-learning/modules
|
||||||
47|
|
47|
|
||||||
48|# Step 3: Start with Module 1
|
48|# Step 3: Start with Module 1
|
||||||
49|python module01_fundamentals.py
|
49|python module01_fundamentals.py
|
||||||
50|```
|
50|```
|
||||||
51|
|
51|
|
||||||
52|## Example Agent Collaboration
|
52|## Example Agent Collaboration
|
||||||
53|
|
53|
|
||||||
54|```python
|
54|```python
|
||||||
55|from openmaic.core import Orchestrator, Agent
|
55|from openmaic.core import Orchestrator, Agent
|
||||||
56|
|
56|
|
||||||
57|# Initialize orchestrator
|
57|# Initialize orchestrator
|
||||||
58|orchestrator = Orchestrator(
|
58|orchestrator = Orchestrator(
|
||||||
59| max_agents=3,
|
59| max_agents=3,
|
||||||
60| collaboration_mode="sequential"
|
60| collaboration_mode="sequential"
|
||||||
61|)
|
61|)
|
||||||
62|
|
62|
|
||||||
63|# Create agents
|
63|# Create agents
|
||||||
64|researcher = Agent(name="researcher", role="Research Assistant")
|
64|researcher = Agent(name="researcher", role="Research Assistant")
|
||||||
65|analyst = Agent(name="analyst", role="Data Analysis")
|
65|analyst = Agent(name="analyst", role="Data Analysis")
|
||||||
66|writer = Agent(name="writer", role="Content Generator")
|
66|writer = Agent(name="writer", role="Content Generator")
|
||||||
67|
|
67|
|
||||||
68|# Execute workflow
|
68|# Execute workflow
|
||||||
69|result = orchestrator.run([
|
69|result = orchestrator.run([
|
||||||
70| researcher.run(task="Research AI trends"),
|
70| researcher.run(task="Research AI trends"),
|
||||||
71| analyst.run(task="Analyze market data"),
|
71| analyst.run(task="Analyze market data"),
|
||||||
72| writer.run(task="Write market report")
|
72| writer.run(task="Write market report")
|
||||||
73|])
|
73|])
|
||||||
74|```
|
74|```
|
||||||
75|
|
75|
|
||||||
76|## Use Cases at Syslog GH/LLC
|
76|## Use Cases at Syslog GH/LLC
|
||||||
77|
|
77|
|
||||||
78|- **Market Research Automation:** Automatically gather and analyze SMB AI adoption data
|
78|- **Market Research Automation:** Automatically gather and analyze SMB AI adoption data
|
||||||
79|- **Content Generation:** Create service descriptions and case studies
|
79|- **Content Generation:** Create service descriptions and case studies
|
||||||
80|- **Customer Support:** Multi-agent Q&A for client inquiries
|
80|- **Customer Support:** Multi-agent Q&A for client inquiries
|
||||||
81|- **Code Review Agents:** Automated code quality checks
|
81|- **Code Review Agents:** Automated code quality checks
|
||||||
82|
|
82|
|
||||||
83|## Related Resources
|
83|## Related Resources
|
||||||
84|
|
84|
|
||||||
85|- **[Autonomous AI Agents](../04\ -\ Autonomous\ AI\ Agents/)** — Advanced workflows
|
85|- **[Autonomous AI Agents](../04\ -\ Autonomous\ AI\ Agents/)** — Advanced workflows
|
||||||
86|- **[Claude Code & Opencode](../01\ -\ Claude\ Code\ \&\ Opencode/)** — Practical implementation
|
86|- **[Claude Code & Opencode](../01\ -\ Claude\ Code\ \&\ Opencode/)** — Practical implementation
|
||||||
87|- **[MCP (Model Context Protocol)](../03\ -\ MCP\ \(Model\ Context\ Protocol\)/)** — Tool integration
|
87|- **[MCP (Model Context Protocol)](../03\ -\ MCP\ \(Model\ Context\ Protocol\)/)** — Tool integration
|
||||||
88|
|
88|
|
||||||
89|---
|
89|---
|
||||||
90|
|
90|
|
||||||
91|*Perfect for Jerome & Theodore's strategy sessions on AI agent frameworks and multi-agent collaboration patterns. This curriculum supports our mission to educate SMBs on AI adoption while building our own agent capabilities.*
|
91|*Perfect for Jerome & Theodore's strategy sessions on AI agent frameworks and multi-agent collaboration patterns. This curriculum supports our mission to educate SMBs on AI adoption while building our own agent capabilities.*
|
||||||
92|
|
92|
|
||||||
-19
@@ -1,19 +0,0 @@
|
|||||||
1|# 03 - AI AGENTS & LEARNING — Home
|
|
||||||
2|**Purpose:** AI agent frameworks, learning resources, and implementation guides.
|
|
||||||
3|
|
|
||||||
4|## Contents
|
|
||||||
5|
|
|
||||||
6|### **01 - Claude Code & Opencode** — Agent framework tutorials and best practices.
|
|
||||||
7|
|
|
||||||
8|### **02 - OpenClaw Framework** — Open-source agent orchestration platform setup and usage.
|
|
||||||
9|
|
|
||||||
10|### **03 - MCP (Model Context Protocol)** — Integration guides for connecting LLMs to external tools and data sources.
|
|
||||||
11|
|
|
||||||
12|### **04 - Autonomous AI Agents** — Research and implementation of autonomous agent workflows.
|
|
||||||
13|
|
|
||||||
14|### **05 - Agent Research & Learning** — Papers, YouTube tutorials, podcasts, and general learning resources.
|
|
||||||
15|
|
|
||||||
16|---
|
|
||||||
17|
|
|
||||||
18|*This section pairs conceptual guides with their implementation scripts for rapid prototyping and deployment.*
|
|
||||||
19|
|
|
||||||
-43
@@ -1,43 +0,0 @@
|
|||||||
1|# 04 - Qwen3.5 Model Setup — Home
|
|
||||||
2|**Purpose:** Installation and configuration guides for Qwen3.5 model variants.
|
|
||||||
3|
|
|
||||||
4|## Available Models
|
|
||||||
5|
|
|
||||||
6|### **Qwen3.5-MoE (Mixture of Experts)** — Optimized for production inference with dynamic expert routing.
|
|
||||||
7|
|
|
||||||
8|### **Qwen3.5-Base** — Standard dense model variant.
|
|
||||||
9|
|
|
||||||
10|### **Qwen3.5-FineTuned** — Domain-specific fine-tuned variants.
|
|
||||||
11|
|
|
||||||
12|## GPU Compatibility
|
|
||||||
13|
|
|
||||||
14|- **AMD Strix Halo** — See [AMD GPU Passthrough Guide](../03\ -\ AMD\ GPU\ Passthrough/00\ -\ AMD\ GPU\ Passthrough.md)
|
|
||||||
15|- **NVIDIA RTX 4090** — Standard CUDA setup
|
|
||||||
16|- **Multi-GPU Clusters** — Distributed inference setup
|
|
||||||
17|
|
|
||||||
18|## Quick Start
|
|
||||||
19|
|
|
||||||
20|### Install Qwen3.5-MoE via Ollama
|
|
||||||
21|```bash
|
|
||||||
22|ollama pull qwen3.5:250b-moe
|
|
||||||
23|ollama serve
|
|
||||||
24|
|
|
||||||
25|# Run locally at 192.168.68.8:8080
|
|
||||||
26|ollama run qwen3.5:250b-moe "What are the top AI trends for 2026?"
|
|
||||||
27|```
|
|
||||||
28|
|
|
||||||
29|### Advanced Configuration
|
|
||||||
30|
|
|
||||||
31|For production deployments with dynamic expert selection:
|
|
||||||
32|- See `/60\ -\ Syslog/02\ -\ TECHNICAL\ INFRASTRUCTURE/04\ -\ Qwen3.5\ Model\ Setup/01\ -\ Qwen3.5-MoE\ Configuration.md`
|
|
||||||
33|- GPU passthrough: `/60\ -\ Syslog/02\ -\ TECHNICAL\ INFRASTRUCTURE/03\ -\ AMD\ GPU\ Passthrough/00\ -\ AMD\ GPU\ Passthrough.md`
|
|
||||||
34|
|
|
||||||
35|## Scripts
|
|
||||||
36|
|
|
||||||
37|- `vulkan-qwen35-moe-setup.sh` — Complete setup script for Qwen3.5-MoE with Vulkan backend
|
|
||||||
38|- `qwen35-moe-inference-config.sh` — Production inference configuration script
|
|
||||||
39|
|
|
||||||
40|---
|
|
||||||
41|
|
|
||||||
42|*For AMD GPU-specific setup, refer to the AMD GPU Passthrough guide.*
|
|
||||||
43|
|
|
||||||
-54
@@ -1,54 +0,0 @@
|
|||||||
1|# 05 - Agent Research & Learning — Home
|
|
||||||
2|**Purpose:** Research papers, tutorials, and resources for AI agent development.
|
|
||||||
3|
|
|
||||||
4|## Overview
|
|
||||||
5|
|
|
||||||
6|Stay current with the latest developments in AI agent technology through curated research, tutorials, and community resources.
|
|
||||||
7|
|
|
||||||
8|## Learning Resources
|
|
||||||
9|
|
|
||||||
10|### **Academic Papers**
|
|
||||||
11|- **Multi-Agent Systems:** Foundations and applications
|
|
||||||
12|- **Reinforcement Learning for Agents:** Q-learning, PPO, GRPO
|
|
||||||
13|- **Agent Communication Protocols:** FIPA, ACL, custom protocols
|
|
||||||
14|- **Tool Learning:** In-context learning for tool selection
|
|
||||||
15|
|
|
||||||
16|### **Video Tutorials**
|
|
||||||
17|- **YouTube Series:** Deep dives into agent architectures
|
|
||||||
18|- **Conference Keynotes:** NeurIPS, ICML, ICLR talks
|
|
||||||
19|- **Hands-on Labs:** Step-by-step implementation guides
|
|
||||||
20|
|
|
||||||
21|### **Podcasts**
|
|
||||||
22|- **AI Agent Deep Dives:** Interviews with researchers
|
|
||||||
23|- **Industry Applications:** Real-world use cases
|
|
||||||
24|- **Future Trends:** Expert predictions and analysis
|
|
||||||
25|
|
|
||||||
26|### **Community Resources**
|
|
||||||
27|- **GitHub Repositories:** Open-source agent frameworks
|
|
||||||
28|- **Discord Servers:** Community support and collaboration
|
|
||||||
29|- **Conferences:** Annual meetups and workshops
|
|
||||||
30|
|
|
||||||
31|## Recommended Reading
|
|
||||||
32|
|
|
||||||
33|1. **"Language Models as Zero-Shot Planners"** — arXiv:2106.04415
|
|
||||||
34|2. **"ReAct: Synergizing Reasoning and Acting"** — arXiv:2210.03629
|
|
||||||
35|3. **"Tool Learning: LLMs Learning to Call External APIs"** — arXiv:2302.04762
|
|
||||||
36|4. **"Multi-Agent Collaboration: A Survey"** — arXiv:2310.08056
|
|
||||||
37|
|
|
||||||
38|## Stay Updated
|
|
||||||
39|
|
|
||||||
40|- **arXiv Alerts:** Set up daily/weekly digests for "agent" papers
|
|
||||||
41|- **Twitter/X:** Follow key researchers and AI labs
|
|
||||||
42|- **GitHub Topics:** #ai-agents, #multi-agent, #agent-orchestration
|
|
||||||
43|- **Newsletter:** AI Weekly, Towards Data Science, ML News
|
|
||||||
44|
|
|
||||||
45|## Related Frameworks
|
|
||||||
46|
|
|
||||||
47|- **[Claude Code & Opencode](../01\ -\ Claude\ Code\ \&\ Opencode/)** — Practical implementation
|
|
||||||
48|- **[OpenClaw Framework](../02\ -\ OpenClaw\ Framework/)** — Production orchestration
|
|
||||||
49|- **[OpenMAIC Education](../06\ -\ OpenMAIC\ Education/)** — Structured learning
|
|
||||||
50|
|
|
||||||
51|---
|
|
||||||
52|
|
|
||||||
53|*Continuous learning resources for Jerome & Theodore to stay ahead in AI agent development.*
|
|
||||||
54|
|
|
||||||
@@ -1,44 +0,0 @@
|
|||||||
1|# 05 - AWS Cloud Infrastructure — Home
|
|
||||||
2|**Purpose:** AWS architecture, networking, and cost optimization for AI workloads.
|
|
||||||
3|
|
|
||||||
4|## Overview
|
|
||||||
5|
|
|
||||||
6|This section covers our AWS cloud infrastructure setup for scalable AI services, including:
|
|
||||||
7|- VPC networking architecture
|
|
||||||
8|- EC2 instance optimization for GPU workloads
|
|
||||||
9|- S3 data pipeline automation
|
|
||||||
10|- Cost optimization strategies
|
|
||||||
11|
|
|
||||||
12|## Infrastructure Components
|
|
||||||
13|
|
|
||||||
14|### **AWS Architecture**
|
|
||||||
15|- **US-East-1 (N. Virginia):** Primary production environment
|
|
||||||
16|- **Multi-AZ deployment:** High availability for critical services
|
|
||||||
17|- **VPC networking:** Isolated subnets for compute, storage, and monitoring
|
|
||||||
18|
|
|
||||||
19|### **Compute Resources**
|
|
||||||
20|- **p4d.24xlarge:** A100-based instances for training
|
|
||||||
21|- **g5.xlarge:** A10 instances for inference
|
|
||||||
22|- **m5.large:** CPU-based instances for web services
|
|
||||||
23|- **Spot instances:** Cost savings for non-critical workloads
|
|
||||||
24|
|
|
||||||
25|### **Storage**
|
|
||||||
26|- **S3 buckets:** Model weights, datasets, backup archives
|
|
||||||
27|- **EBS volumes:** High-performance storage for active VMs
|
|
||||||
28|- **Glacier:** Cold storage for historical data
|
|
||||||
29|
|
|
||||||
30|## Cost Optimization
|
|
||||||
31|
|
|
||||||
32|- **Reserved Instances:** 1-3 year commitments for baseline workloads
|
|
||||||
33|- **Spot Instances:** 70% savings for fault-tolerant tasks
|
|
||||||
34|- **S3 Lifecycle Policies:** Automatic tiering to Glacier
|
|
||||||
35|- **CloudWatch Alarms:** Budget alerts and anomaly detection
|
|
||||||
36|
|
|
||||||
37|## Related Documents
|
|
||||||
38|
|
|
||||||
39|- **[Qwen3.5-MoE Setup](../02\ -\ TECHNICAL\ INFRASTRUCTURE/04\ -\ Qwen3.5\ Model\ Setup/)** — Model deployment strategies
|
|
||||||
40|
|
|
||||||
41|---
|
|
||||||
42|
|
|
||||||
43|*Our AWS infrastructure supports our SMB AI services and agent deployments with maximum efficiency.*
|
|
||||||
44|
|
|
||||||
-86
@@ -1,86 +0,0 @@
|
|||||||
1|# 02 - TECHNICAL INFRASTRUCTURE — Overview
|
|
||||||
2|**Purpose:** Complete technical guide for Syslog infrastructure, GPU passthrough, and model deployment.
|
|
||||||
3|
|
|
||||||
4|## Infrastructure Components
|
|
||||||
5|
|
|
||||||
6|### **01 - Proxmox & VM Passthrough**
|
|
||||||
7|- GPU passthrough configuration (AMD/Intel)
|
|
||||||
8|- VM networking setup
|
|
||||||
9|- Resource allocation best practices
|
|
||||||
10|
|
|
||||||
11|### **02 - GPU Monitoring**
|
|
||||||
12|- Grafana dashboards for GPU telemetry
|
|
||||||
13|- ROCm monitoring setup
|
|
||||||
14|- Real-time performance tracking
|
|
||||||
15|
|
|
||||||
16|### **03 - AMD GPU Passthrough (Strix Halo)**
|
|
||||||
17|- Detailed AMD APU passthrough for host LLM access
|
|
||||||
18|- Vulkan driver configuration
|
|
||||||
19|- HIP SDK integration
|
|
||||||
20|
|
|
||||||
21|### **04 - Qwen3.5 Model Setup**
|
|
||||||
22|- Qwen3.5-MoE (Mixture of Experts) installation
|
|
||||||
23|- Vulkan backend optimization
|
|
||||||
24|- Production inference configuration
|
|
||||||
25|
|
|
||||||
26|### **05 - AWS Cloud Infrastructure**
|
|
||||||
27|- VPC and networking architecture
|
|
||||||
28|- EC2 instance configuration for AI workloads
|
|
||||||
29|- S3 data pipeline setup
|
|
||||||
30|- Cost optimization strategies
|
|
||||||
31|
|
|
||||||
32|## Deployment Standards
|
|
||||||
33|
|
|
||||||
34|- **GPU Access:** AMD Strix Halo for host inference, NVIDIA for training
|
|
||||||
35|- **Model Hosting:** Ollama local deployment @ 192.168.68.8:8080
|
|
||||||
36|- **Cloud:** AWS for scalable cloud workloads
|
|
||||||
37|- **Storage:** S3 for model weights and datasets
|
|
||||||
38|- **Monitoring:** Grafana + Prometheus for observability
|
|
||||||
39|
|
|
||||||
40|## Common Operations
|
|
||||||
41|
|
|
||||||
42|### Start Qwen3.5-MoE
|
|
||||||
43|```bash
|
|
||||||
44|ollama pull qwen3.5:250b-moe
|
|
||||||
45|ollama serve --model qwen3.5:250b-moe
|
|
||||||
46|```
|
|
||||||
47|
|
|
||||||
48|### Check GPU Status
|
|
||||||
49|```bash
|
|
||||||
50|# AMD
|
|
||||||
51|rocm-smi
|
|
||||||
52|watch -n 5 rocm-smi
|
|
||||||
53|
|
|
||||||
54|# NVIDIA
|
|
||||||
55|nvidia-smi
|
|
||||||
56|watch -n 5 nvidia-smi
|
|
||||||
57|```
|
|
||||||
58|
|
|
||||||
59|### Deploy New Agent
|
|
||||||
60|```bash
|
|
||||||
61|# Clone agent repository
|
|
||||||
62|git clone https://github.com/sysloggh/agent-template.git
|
|
||||||
63|cd agent-template
|
|
||||||
64|
|
|
||||||
65|# Configure environment
|
|
||||||
66|cp .env.example .env
|
|
||||||
67|# Edit .env with API keys and settings
|
|
||||||
68|
|
|
||||||
69|# Install dependencies
|
|
||||||
70|pip install -r requirements.txt
|
|
||||||
71|
|
|
||||||
72|# Deploy
|
|
||||||
73|source venv/bin/activate
|
|
||||||
74|python main.py
|
|
||||||
75|```
|
|
||||||
76|
|
|
||||||
77|## Related Documentation
|
|
||||||
78|
|
|
||||||
79|- [Business Strategy](../01\ -\ BUSINESS\ \&\ STRATEGY/00\ -\ Business Strategy Home.md)
|
|
||||||
80|- [AI Agents Framework](../03\ -\ AI\ AGENTS\ \&\ LEARNING/00\ -\ AI Agents Learning Home.md)
|
|
||||||
81|- [Operational Excellence](../05\ -\ OPERATIONAL\ EXCELLENCE/00\ -\ Operational Excellence Home.md)
|
|
||||||
82|
|
|
||||||
83|---
|
|
||||||
84|
|
|
||||||
85|*This section pairs implementation guides with their respective scripts for rapid deployment.*
|
|
||||||
86|
|
|
||||||
@@ -1,51 +0,0 @@
|
|||||||
1|# 02 - GPU Monitoring — Home
|
|
||||||
2|**Purpose:** Grafana dashboards and monitoring setup for GPU telemetry.
|
|
||||||
3|
|
|
||||||
4|## Contents
|
|
||||||
5|
|
|
||||||
6|This directory contains:
|
|
||||||
7|- Grafana dashboard configuration
|
|
||||||
8|- ROCm monitoring setup
|
|
||||||
9|- Real-time performance tracking
|
|
||||||
10|
|
|
||||||
11|### Monitoring Features
|
|
||||||
12|
|
|
||||||
13|- **Real-time GPU utilization:** Track VRAM, compute, and memory usage
|
|
||||||
14|- **Temperature monitoring:** Alert on overheating conditions
|
|
||||||
15|- **Performance metrics:** Core clock, power consumption, fan speeds
|
|
||||||
16|- **Historical data:** Grafana time-series graphs for trend analysis
|
|
||||||
17|
|
|
||||||
18|## Quick Start
|
|
||||||
19|
|
|
||||||
20|### Grafana Dashboard Setup
|
|
||||||
21|
|
|
||||||
22|```bash
|
|
||||||
23|# Install Grafana
|
|
||||||
24|sudo apt install grafana
|
|
||||||
25|
|
|
||||||
26|# Start Grafana service
|
|
||||||
27|systemctl start grafana-server
|
|
||||||
28|
|
|
||||||
29|# Access dashboard
|
|
||||||
30|# http://localhost:3000 (admin/admin)
|
|
||||||
31|```
|
|
||||||
32|
|
|
||||||
33|### ROCm Monitoring
|
|
||||||
34|
|
|
||||||
35|```bash
|
|
||||||
36|# Install ROCm health monitoring tools
|
|
||||||
37|sudo apt install rocminfo rocm-smi
|
|
||||||
38|
|
|
||||||
39|# Real-time monitoring
|
|
||||||
40|watch -n 1 rocm-smi
|
|
||||||
41|```
|
|
||||||
42|
|
|
||||||
43|## Related Infrastructure
|
|
||||||
44|
|
|
||||||
45|- **[AMD GPU Passthrough](../03\ -\ AMD\ GPU\ Passthrough/)** — Hardware configuration
|
|
||||||
46|- **[Qwen3.5 Model Setup](../04\ -\ Qwen3.5\ Model\ Setup/)** — Model deployment
|
|
||||||
47|
|
|
||||||
48|---
|
|
||||||
49|
|
|
||||||
50|*Monitor your GPUs 24/7 to ensure optimal performance for LLM inference workloads.*
|
|
||||||
51|
|
|
||||||
-47
@@ -1,47 +0,0 @@
|
|||||||
1|# 01 - Proxmox & VM Passthrough — Home
|
|
||||||
2|**Purpose:** Complete setup guide for Proxmox VM passthrough with optimal resource allocation.
|
|
||||||
3|
|
|
||||||
4|## Topics Covered
|
|
||||||
5|
|
|
||||||
6|- **GPU Passthrough:** Configure AMD/Intel/NVIDIA GPUs for VM access
|
|
||||||
7|- **NVMe Passthrough:** Pass NVMe drives to VMs for high I/O performance
|
|
||||||
8|- **USB Passthrough:** Connect USB devices (webcams, dongles, etc.) to VMs
|
|
||||||
9|- **Networking:** Bridge networking, VLANs, and virtual switches
|
|
||||||
10|- **Resource Allocation:** CPU cores, RAM, and storage optimization
|
|
||||||
11|
|
|
||||||
12|## Related Guides
|
|
||||||
13|
|
|
||||||
14|- **[00 - Proxmox & VM Passthrough](00 - Proxmox & VM Passthrough.md)** — This overview document
|
|
||||||
15|- **[03 - AMD GPU Passthrough](../03\ -\ AMD\ GPU\ Passthrough/)** — AMD-specific setup
|
|
||||||
16|
|
|
||||||
17|## Quick Start
|
|
||||||
18|
|
|
||||||
19|### Create a VM with GPU Passthrough
|
|
||||||
20|
|
|
||||||
21|```bash
|
|
||||||
22|# Step 1: Find available GPU
|
|
||||||
23|rocm-smi | grep "GPU" # AMD
|
|
||||||
24|nvidia-smi # NVIDIA
|
|
||||||
25|
|
|
||||||
26|# Step 2: Create VM with GPU passthrough
|
|
||||||
27|qm create 100 --name qwen-vm --memory 32768 --cores 8 --arch x86_64
|
|
||||||
28|qm set 100 --hostpci0=0000:03:00.0,pcie=1,x-vga=1 # AMD example
|
|
||||||
29|
|
|
||||||
30|# Step 3: Install QEMU Guest Agent
|
|
||||||
31|apt install qemu-guest-agent
|
|
||||||
32|
|
|
||||||
33|# Step 4: Reboot VM
|
|
||||||
34|qm reboot 100
|
|
||||||
35|```
|
|
||||||
36|
|
|
||||||
37|## Best Practices
|
|
||||||
38|
|
|
||||||
39|1. **IOMMU Groups:** Always check if devices are in separate IOMMU groups
|
|
||||||
40|2. **VFIO Modules:** Ensure `vfio-pci` module is loaded before boot
|
|
||||||
41|3. **PCIe Hotplug:** Disable for stability unless required
|
|
||||||
42|4. **Memory Ballooning:** Disable in VM for consistent performance
|
|
||||||
43|
|
|
||||||
44|---
|
|
||||||
45|
|
|
||||||
46|*This guide is essential for GPU passthrough to VMs running LLM inference workloads.*
|
|
||||||
47|
|
|
||||||
@@ -1,56 +0,0 @@
|
|||||||
1|# 03 - AMD GPU Passthrough (Strix Halo) — Home
|
|
||||||
2|**Purpose:** Detailed AMD APU passthrough configuration for host LLM access.
|
|
||||||
3|
|
|
||||||
4|## Overview
|
|
||||||
5|
|
|
||||||
6|This guide covers the complete setup for AMD Strix Halo GPU passthrough, enabling native LLM inference on AMD hardware.
|
|
||||||
7|
|
|
||||||
8|## What You'll Learn
|
|
||||||
9|
|
|
||||||
10|- **Hardware preparation:** Verify Strix Halo compatibility
|
|
||||||
11|- **BIOS configuration:** Enable IOMMU and PCIe passthrough
|
|
||||||
12|- **Kernel configuration:** Load VFIO modules properly
|
|
||||||
13|- **Proxmox setup:** Configure GPU for VM passthrough
|
|
||||||
14|- **Driver installation:** Vulkan, ROCm, HIP SDK integration
|
|
||||||
15|- **Qwen3.5-MoE setup:** Configure for AMD GPU acceleration
|
|
||||||
16|
|
|
||||||
17|## Prerequisites
|
|
||||||
18|
|
|
||||||
19|- AMD Strix Halo APU with integrated Radeon graphics
|
|
||||||
20|- Linux system kernel 5.4+ with IOMMU support
|
|
||||||
21|- Proxmox VE 7.x or later
|
|
||||||
22|- 16GB+ system RAM (8GB for APU graphics, 8GB for OS)
|
|
||||||
23|- SSD storage for VM images
|
|
||||||
24|
|
|
||||||
25|## Quick Start
|
|
||||||
26|
|
|
||||||
27|```bash
|
|
||||||
28|# Enable IOMMU in GRUB
|
|
||||||
29|# Edit /etc/default/grub, add:
|
|
||||||
30|# GRUB_CMDLINE_LINUX="amd_iommu=on iommu=pt"
|
|
||||||
31|
|
|
||||||
32|# Update GRUB
|
|
||||||
33|update-grub
|
|
||||||
34|
|
|
||||||
35|# Load VFIO modules
|
|
||||||
36|echo "vfio
|
|
||||||
37|vfio_iommu_type1
|
|
||||||
38|vfio_pci
|
|
||||||
39|vfio_virqfd" | sudo tee /etc/modules-load.d/vfio.conf
|
|
||||||
40|
|
|
||||||
41|# Blacklist Radeon in VM
|
|
||||||
42|modprobe -r radeon amdgpu
|
|
||||||
43|
|
|
||||||
44|# Reboot to apply changes
|
|
||||||
45|reboot
|
|
||||||
46|```
|
|
||||||
47|
|
|
||||||
48|## Related Guides
|
|
||||||
49|
|
|
||||||
50|- **[01 - Proxmox & VM Passthrough](../01\ -\ Proxmox\ \&\ VM\ Passthrough/)** — General passthrough setup
|
|
||||||
51|- **[04 - Qwen3.5 Model Setup](../04\ -\ Qwen3.5\ Model\ Setup/)** — Model deployment
|
|
||||||
52|
|
|
||||||
53|---
|
|
||||||
54|
|
|
||||||
55|*Essential for running Qwen3.5-MoE locally on AMD hardware with Vulkan backend acceleration.*
|
|
||||||
56|
|
|
||||||
@@ -1,34 +0,0 @@
|
|||||||
# 03 Operations
|
|
||||||
|
|
||||||
## 📋 Overview
|
|
||||||
This section contains operational procedures, client onboarding, support processes, and quality assurance.
|
|
||||||
|
|
||||||
## 🚧 Under Construction
|
|
||||||
This documentation section is currently being developed. Content will be added as part of the repository reorganization project.
|
|
||||||
|
|
||||||
## 📁 Planned Structure
|
|
||||||
```
|
|
||||||
03-operations/
|
|
||||||
├── README.md # This file
|
|
||||||
├── [content directories] # To be defined
|
|
||||||
└── [template files] # To be defined
|
|
||||||
```
|
|
||||||
|
|
||||||
## 🎯 Objectives
|
|
||||||
- [ ] Define section structure
|
|
||||||
- [ ] Create comprehensive documentation
|
|
||||||
- [ ] Develop templates and standards
|
|
||||||
- [ ] Integrate with overall documentation system
|
|
||||||
|
|
||||||
## 📅 Timeline
|
|
||||||
- **Start Date**: April 2026
|
|
||||||
- **Target Completion**: May 2026
|
|
||||||
- **Owner**: Jerome Tabiri
|
|
||||||
|
|
||||||
## 🔗 Related Sections
|
|
||||||
- Check other documentation sections for completed content
|
|
||||||
- Refer to the root README for overall repository structure
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
*This documentation section is under development as part of Syslog Solution LLC's repository reorganization project.*
|
|
||||||
@@ -1,93 +0,0 @@
|
|||||||
# Documentation Migration Summary
|
|
||||||
|
|
||||||
## 📊 Migration Statistics
|
|
||||||
- **Total files migrated**: 1
|
|
||||||
- **Original public repo files**: 18
|
|
||||||
- **Migration completion**: 5%
|
|
||||||
|
|
||||||
## 📁 Sections Created
|
|
||||||
|
|
||||||
### 01-business-strategy/ (0 files)
|
|
||||||
- Business vision and mission
|
|
||||||
- Market analysis and positioning
|
|
||||||
- Financial projections
|
|
||||||
- Marketing materials
|
|
||||||
|
|
||||||
### 02-technical-architecture/ (0 files)
|
|
||||||
- Infrastructure overview
|
|
||||||
- AWS architecture
|
|
||||||
- Proxmox cluster documentation
|
|
||||||
- AI agents framework
|
|
||||||
- Deployment standards
|
|
||||||
- Security and compliance
|
|
||||||
- Monitoring and logging
|
|
||||||
|
|
||||||
### 03-operations/ (0 files)
|
|
||||||
- Client onboarding
|
|
||||||
- Support processes
|
|
||||||
- Incident response
|
|
||||||
- Quality assurance
|
|
||||||
|
|
||||||
### 04-customer-portal/ (0 files)
|
|
||||||
- Placeholder - to be developed
|
|
||||||
|
|
||||||
### 05-development/ (0 files)
|
|
||||||
- Placeholder - to be developed
|
|
||||||
|
|
||||||
### templates/ (0 files)
|
|
||||||
- Placeholder - to be developed
|
|
||||||
|
|
||||||
## 🔄 Migration Details
|
|
||||||
|
|
||||||
### Source Repository
|
|
||||||
- **Location**: /root/hermes-workspace/projects/syslog-solution/syslogsolution-repo/
|
|
||||||
- **Structure**: Numbered documentation sections (01-, 02-, etc.)
|
|
||||||
- **Content**: Business, technical, AI agents, operations documentation
|
|
||||||
|
|
||||||
### Target Structure
|
|
||||||
- **Location**: /root/syslogsolution/documentation/
|
|
||||||
- **Structure**: Thematic organization with clear naming
|
|
||||||
- **Improvements**:
|
|
||||||
- Better categorization of content
|
|
||||||
- Consistent naming conventions
|
|
||||||
- Clear separation of concerns
|
|
||||||
- Scalable structure for future growth
|
|
||||||
|
|
||||||
## 🎯 Next Steps for Documentation
|
|
||||||
|
|
||||||
### Immediate (Week 1)
|
|
||||||
1. **Review migrated content** - Ensure all important information was transferred
|
|
||||||
2. **Fix broken links** - Update any internal references
|
|
||||||
3. **Standardize formatting** - Apply consistent markdown style
|
|
||||||
4. **Add missing content** - Fill gaps in documentation
|
|
||||||
|
|
||||||
### Short-term (Week 2)
|
|
||||||
1. **Develop customer portal documentation** (04-customer-portal/)
|
|
||||||
2. **Create development standards** (05-development/)
|
|
||||||
3. **Build documentation templates** (templates/)
|
|
||||||
4. **Implement search functionality**
|
|
||||||
|
|
||||||
### Medium-term (Week 3-4)
|
|
||||||
1. **Add visual diagrams and screenshots**
|
|
||||||
2. **Create video tutorials**
|
|
||||||
3. **Implement versioning for documentation**
|
|
||||||
4. **Set up automated documentation builds**
|
|
||||||
|
|
||||||
## 📝 Notes
|
|
||||||
- Migration completed on: April 10, 2026
|
|
||||||
- Migrated by: Mumuni (SucciBot)
|
|
||||||
- Review required by: Jerome Tabiri
|
|
||||||
- Next review date: April 17, 2026
|
|
||||||
|
|
||||||
## ✅ Quality Checklist
|
|
||||||
- [ ] All critical business documentation migrated
|
|
||||||
- [ ] Technical architecture fully documented
|
|
||||||
- [ ] AI agents framework properly organized
|
|
||||||
- [ ] Operational procedures in place
|
|
||||||
- [ ] No broken links in migrated content
|
|
||||||
- [ ] Consistent formatting applied
|
|
||||||
- [ ] README files updated for each section
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
*This summary is part of the Syslog Solution LLC repository reorganization project.*
|
|
||||||
@@ -1,34 +0,0 @@
|
|||||||
# Templates
|
|
||||||
|
|
||||||
## 📋 Overview
|
|
||||||
This section contains documentation templates, proposal templates, meeting notes templates, and report templates.
|
|
||||||
|
|
||||||
## 🚧 Under Construction
|
|
||||||
This documentation section is currently being developed. Content will be added as part of the repository reorganization project.
|
|
||||||
|
|
||||||
## 📁 Planned Structure
|
|
||||||
```
|
|
||||||
templates/
|
|
||||||
├── README.md # This file
|
|
||||||
├── [content directories] # To be defined
|
|
||||||
└── [template files] # To be defined
|
|
||||||
```
|
|
||||||
|
|
||||||
## 🎯 Objectives
|
|
||||||
- [ ] Define section structure
|
|
||||||
- [ ] Create comprehensive documentation
|
|
||||||
- [ ] Develop templates and standards
|
|
||||||
- [ ] Integrate with overall documentation system
|
|
||||||
|
|
||||||
## 📅 Timeline
|
|
||||||
- **Start Date**: April 2026
|
|
||||||
- **Target Completion**: April 2026
|
|
||||||
- **Owner**: Jerome Tabiri
|
|
||||||
|
|
||||||
## 🔗 Related Sections
|
|
||||||
- Check other documentation sections for completed content
|
|
||||||
- Refer to the root README for overall repository structure
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
*This documentation section is under development as part of Syslog Solution LLC's repository reorganization project.*
|
|
||||||
@@ -0,0 +1,182 @@
|
|||||||
|
#!/bin/bash
|
||||||
|
# OpenMAIC Education Setup Script
|
||||||
|
# Purpose: Deploy OpenMAIC (Open Multi-Agent AI Collaboration) educational environment
|
||||||
|
# Version: 1.0.0
|
||||||
|
|
||||||
|
set -e
|
||||||
|
|
||||||
|
echo "=== OpenMAIC Educational Environment Setup ==="
|
||||||
|
|
||||||
|
# Configuration
|
||||||
|
OPENMAIC_DIR="${HOME}/projects/openmaic"
|
||||||
|
EDUCATION_DIR="${OPENMAIC_DIR}/education"
|
||||||
|
|
||||||
|
# Create directory structure
|
||||||
|
echo "Setting up OpenMAIC directory structure..."
|
||||||
|
mkdir -p "$OPENMAIC_DIR"
|
||||||
|
mkdir -p "$EDUCATION_DIR/curriculum"
|
||||||
|
mkdir -p "$EDUCATION_DIR/demos"
|
||||||
|
mkdir -p "$EDUCATION_DIR/tutorials"
|
||||||
|
|
||||||
|
# Install OpenMAIC core
|
||||||
|
echo "Installing OpenMAIC framework..."
|
||||||
|
pip install openmaic-core openmaic-editor openmaic-visualizer
|
||||||
|
|
||||||
|
# Create sample agent definitions for education
|
||||||
|
echo "Creating educational agent examples..."
|
||||||
|
cat > "$EDUCATION_DIR/curriculum/agent1_basic_researcher.json" << 'EOF'
|
||||||
|
{
|
||||||
|
"name": "researcher",
|
||||||
|
"role": "Research Assistant",
|
||||||
|
"capabilities": ["web_search", "data_analysis", "summarization"],
|
||||||
|
"context_window": 8192,
|
||||||
|
"model": "qwen3.5:35b"
|
||||||
|
}
|
||||||
|
EOF
|
||||||
|
|
||||||
|
cat > "$EDUCATION_DIR/curriculum/agent2_data_analyst.json" << 'EOF'
|
||||||
|
{
|
||||||
|
"name": "data_analyst",
|
||||||
|
"role": "Data Analysis Specialist",
|
||||||
|
"capabilities": ["pandas", "numpy", "visualization", "statistical_testing"],
|
||||||
|
"context_window": 8192,
|
||||||
|
"model": "qwen3.5:35b"
|
||||||
|
}
|
||||||
|
EOF
|
||||||
|
|
||||||
|
cat > "$EDUCATION_DIR/curriculum/agent3_content_writer.json" << 'EOF'
|
||||||
|
{
|
||||||
|
"name": "content_writer",
|
||||||
|
"role": "Content Generator",
|
||||||
|
"capabilities": ["writing", "editing", "style_transfer"],
|
||||||
|
"context_window": 8192,
|
||||||
|
"model": "qwen3.5:35b"
|
||||||
|
}
|
||||||
|
EOF
|
||||||
|
|
||||||
|
# Create educational demos
|
||||||
|
echo "Creating educational demo workflows..."
|
||||||
|
cat > "$EDUCATION_DIR/demos/agent_collaboration_example.py" << 'EOF'
|
||||||
|
#!/usr/bin/env python3
|
||||||
|
"""
|
||||||
|
OpenMAIC Educational Demo: Multi-Agent Collaboration
|
||||||
|
This demonstrates how agents coordinate to solve complex problems
|
||||||
|
"""
|
||||||
|
|
||||||
|
from openmaic.core import Agent, Orchestrator
|
||||||
|
from openmaic.visualizer import CollaborationVisualizer
|
||||||
|
|
||||||
|
def demonstrate_agent_collaboration():
|
||||||
|
"""Show how agents collaborate to complete a task."""
|
||||||
|
|
||||||
|
# Initialize orchestrator
|
||||||
|
orchestrator = Orchestrator(
|
||||||
|
max_agents=3,
|
||||||
|
collaboration_mode="sequential",
|
||||||
|
output_format="markdown"
|
||||||
|
)
|
||||||
|
|
||||||
|
# Create agents from definitions
|
||||||
|
researcher = Agent.load("$EDUCATION_DIR/curriculum/agent1_basic_researcher.json")
|
||||||
|
analyst = Agent.load("$EDUCATION_DIR/curriculum/agent2_data_analyst.json")
|
||||||
|
writer = Agent.load("$EDUCATION_DIR/curriculum/agent3_content_writer.json")
|
||||||
|
|
||||||
|
# Define collaboration workflow
|
||||||
|
workflow = [
|
||||||
|
{"agent": researcher, "task": "Research AI trends in SMB market"},
|
||||||
|
{"agent": analyst, "task": "Analyze market data and identify opportunities"},
|
||||||
|
{"agent": writer, "task": "Write comprehensive market analysis report"}
|
||||||
|
]
|
||||||
|
|
||||||
|
# Execute and visualize
|
||||||
|
orchestrator.run_workflow(workflow)
|
||||||
|
|
||||||
|
# Display results
|
||||||
|
visualizer = CollaborationVisualizer(orchestrator)
|
||||||
|
print(visualizer.render_collaboration_flow())
|
||||||
|
print(orchestrator.get_final_output())
|
||||||
|
|
||||||
|
return orchestrator.get_results()
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
demonstrate_agent_collaboration()
|
||||||
|
EOF
|
||||||
|
|
||||||
|
chmod +x "$EDUCATION_DIR/demos/agent_collaboration_example.py"
|
||||||
|
|
||||||
|
# Create curriculum documentation
|
||||||
|
echo "Creating curriculum documentation..."
|
||||||
|
cat > "$EDUCATION_DIR/curriculum/README.md" << 'EOF'
|
||||||
|
# OpenMAIC Educational Curriculum
|
||||||
|
|
||||||
|
This curriculum introduces multi-agent AI systems through hands-on projects.
|
||||||
|
|
||||||
|
## Module 1: Fundamentals
|
||||||
|
- Understanding agent roles and capabilities
|
||||||
|
- Basic Orchestrator configuration
|
||||||
|
- Simple agent collaboration patterns
|
||||||
|
|
||||||
|
## Module 2: Advanced Collaboration
|
||||||
|
- Multi-agent workflow design
|
||||||
|
- Context sharing between agents
|
||||||
|
- Error handling and recovery
|
||||||
|
|
||||||
|
## Module 3: Production Patterns
|
||||||
|
- Scaling to 10+ agents
|
||||||
|
- Performance optimization
|
||||||
|
- Monitoring and diagnostics
|
||||||
|
|
||||||
|
## Module 4: Real-World Applications
|
||||||
|
- Market analysis automation
|
||||||
|
- Customer support orchestration
|
||||||
|
- Content pipeline automation
|
||||||
|
|
||||||
|
## Getting Started
|
||||||
|
|
||||||
|
1. Install OpenMAIC: `pip install openmaic-core openmaic-visualizer`
|
||||||
|
2. Review curriculum guides in `/curriculum/`
|
||||||
|
3. Run demo workflows in `/demos/`
|
||||||
|
4. Participate in hands-on exercises
|
||||||
|
|
||||||
|
## Prerequisites
|
||||||
|
- Python 3.10+
|
||||||
|
- Ollama or similar LLM service
|
||||||
|
- Basic understanding of AI/ML concepts
|
||||||
|
EOF
|
||||||
|
|
||||||
|
# Set up virtual environment
|
||||||
|
echo "Creating virtual environment..."
|
||||||
|
python3 -m venv "$OPENMAIC_DIR/venv"
|
||||||
|
source "$OPENMAIC_DIR/venv/bin/activate"
|
||||||
|
pip install openmaic-core openmaic-editor openmaic-visualizer pandas numpy matplotlib
|
||||||
|
|
||||||
|
# Create environment variables
|
||||||
|
cat > "$OPENMAIC_DIR/.env" << 'EOF'
|
||||||
|
# OpenMAIC Configuration
|
||||||
|
OPENMAIC_LOG_LEVEL=INFO
|
||||||
|
OPENMAIC_MAX_CONCURRENT_AGENTS=5
|
||||||
|
OPENMAIC_COLLABORATION_MODE=sequential
|
||||||
|
|
||||||
|
# Model Setup
|
||||||
|
OLLAMA_BASE_URL=http://localhost:11434
|
||||||
|
QWEN35_ENDPOINT=192.168.68.8:8080
|
||||||
|
|
||||||
|
# Collaboration Settings
|
||||||
|
COLLABORATION_CONTEXT_WINDOW=8192
|
||||||
|
COLLABORATION_TIMEOUT=3600
|
||||||
|
EOF
|
||||||
|
|
||||||
|
# Display summary
|
||||||
|
echo ""
|
||||||
|
echo "=== OpenMAIC Education Environment Ready ==="
|
||||||
|
echo "Directory: $OPENMAIC_DIR"
|
||||||
|
echo "Curriculum: $EDUCATION_DIR/curriculum/"
|
||||||
|
echo "Demos: $EDUCATION_DIR/demos/"
|
||||||
|
echo ""
|
||||||
|
echo "To start learning:"
|
||||||
|
echo "1. cd $OPENMAIC_DIR"
|
||||||
|
echo "2. source venv/bin/activate"
|
||||||
|
echo "3. Run demos: python $EDUCATION_DIR/demos/agent_collaboration_example.py"
|
||||||
|
echo "4. Study curriculum guides in $EDUCATION_DIR/curriculum/"
|
||||||
|
echo ""
|
||||||
|
echo "Perfect for Jerome and Theodore's strategy sessions on AI agent frameworks!"
|
||||||
Executable
+95
@@ -0,0 +1,95 @@
|
|||||||
|
#!/bin/bash
|
||||||
|
# Setup script for Syslog Solution LLC AWS Organization Terraform
|
||||||
|
|
||||||
|
set -e # Exit on error
|
||||||
|
|
||||||
|
echo "🚀 Syslog Solution LLC AWS Organization Setup"
|
||||||
|
echo "============================================"
|
||||||
|
|
||||||
|
# Check prerequisites
|
||||||
|
echo "🔍 Checking prerequisites..."
|
||||||
|
|
||||||
|
# Check AWS CLI
|
||||||
|
if ! command -v aws &> /dev/null; then
|
||||||
|
echo "❌ AWS CLI not found. Please install AWS CLI first."
|
||||||
|
echo " Visit: https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html"
|
||||||
|
exit 1
|
||||||
|
fi
|
||||||
|
|
||||||
|
# Check Terraform
|
||||||
|
if ! command -v terraform &> /dev/null; then
|
||||||
|
echo "❌ Terraform not found. Please install Terraform first."
|
||||||
|
echo " Visit: https://developer.hashicorp.com/terraform/tutorials/aws-get-started/install-cli"
|
||||||
|
exit 1
|
||||||
|
fi
|
||||||
|
|
||||||
|
echo "✅ Prerequisites check passed"
|
||||||
|
|
||||||
|
# Configure AWS CLI
|
||||||
|
echo ""
|
||||||
|
echo "🔧 Configuring AWS CLI..."
|
||||||
|
echo "Please enter your AWS credentials for the new business account:"
|
||||||
|
|
||||||
|
read -p "AWS Access Key ID: " AWS_ACCESS_KEY_ID
|
||||||
|
read -p "AWS Secret Access Key: " AWS_SECRET_ACCESS_KEY
|
||||||
|
|
||||||
|
aws configure set aws_access_key_id "$AWS_ACCESS_KEY_ID" --profile syslog-business
|
||||||
|
aws configure set aws_secret_access_key "$AWS_SECRET_ACCESS_KEY" --profile syslog-business
|
||||||
|
aws configure set region "us-east-1" --profile syslog-business
|
||||||
|
aws configure set output "json" --profile syslog-business
|
||||||
|
|
||||||
|
echo "✅ AWS CLI configured with profile 'syslog-business'"
|
||||||
|
|
||||||
|
# Test AWS connection
|
||||||
|
echo ""
|
||||||
|
echo "🔗 Testing AWS connection..."
|
||||||
|
if aws sts get-caller-identity --profile syslog-business &> /dev/null; then
|
||||||
|
echo "✅ AWS connection successful"
|
||||||
|
else
|
||||||
|
echo "❌ AWS connection failed. Please check your credentials."
|
||||||
|
exit 1
|
||||||
|
fi
|
||||||
|
|
||||||
|
# Initialize Terraform
|
||||||
|
echo ""
|
||||||
|
echo "🏗️ Initializing Terraform..."
|
||||||
|
terraform init
|
||||||
|
|
||||||
|
# Copy example variables file
|
||||||
|
echo ""
|
||||||
|
echo "📝 Setting up configuration..."
|
||||||
|
if [ ! -f terraform.tfvars ]; then
|
||||||
|
cp terraform.tfvars.example terraform.tfvars
|
||||||
|
echo "✅ Created terraform.tfvars from example"
|
||||||
|
echo ""
|
||||||
|
echo "⚠️ Please edit terraform.tfvars with your specific values:"
|
||||||
|
echo " - Update email addresses for dev and staging accounts"
|
||||||
|
echo " - Adjust billing alert threshold if needed"
|
||||||
|
echo " - Review other configuration options"
|
||||||
|
echo ""
|
||||||
|
read -p "Press Enter to continue after editing terraform.tfvars..."
|
||||||
|
else
|
||||||
|
echo "✅ terraform.tfvars already exists"
|
||||||
|
fi
|
||||||
|
|
||||||
|
# Show plan
|
||||||
|
echo ""
|
||||||
|
echo "📋 Showing Terraform plan..."
|
||||||
|
terraform plan
|
||||||
|
|
||||||
|
echo ""
|
||||||
|
echo "============================================"
|
||||||
|
echo "🎯 Setup complete! Next steps:"
|
||||||
|
echo ""
|
||||||
|
echo "1. Review the Terraform plan above"
|
||||||
|
echo "2. Apply the configuration:"
|
||||||
|
echo " terraform apply"
|
||||||
|
echo ""
|
||||||
|
echo "3. After applying:"
|
||||||
|
echo " - Check email for AWS account creation invites"
|
||||||
|
echo " - Accept invitations for dev and staging accounts"
|
||||||
|
echo " - Set up AWS IAM Identity Center (SSO)"
|
||||||
|
echo " - Configure AWS profiles for each account"
|
||||||
|
echo ""
|
||||||
|
echo "Need help? Check README.md for detailed instructions."
|
||||||
|
echo "============================================"
|
||||||
@@ -0,0 +1,74 @@
|
|||||||
|
#!/bin/bash
|
||||||
|
# OpenClaw Framework Setup Script
|
||||||
|
# Version: 1.0.0
|
||||||
|
# Purpose: Initialize OpenClaw agent orchestration environment
|
||||||
|
|
||||||
|
set -e
|
||||||
|
|
||||||
|
echo "=== OpenClaw Framework Setup ==="
|
||||||
|
|
||||||
|
# Configuration
|
||||||
|
OPENCLAW_DIR="${HOME}/projects/openclaw"
|
||||||
|
PYTHON_VERSION="3.11"
|
||||||
|
|
||||||
|
# Check Python version
|
||||||
|
echo "Checking Python version..."
|
||||||
|
python3 --version | grep -q "$PYTHON_VERSION" || echo "Warning: Python $PYTHON_VERSION recommended"
|
||||||
|
|
||||||
|
# Create project directory
|
||||||
|
echo "Creating OpenClaw directory..."
|
||||||
|
mkdir -p "$OPENCLAW_DIR"
|
||||||
|
cd "$OPENCLAW_DIR"
|
||||||
|
|
||||||
|
# Initialize Python virtual environment
|
||||||
|
echo "Setting up virtual environment..."
|
||||||
|
python3 -m venv venv
|
||||||
|
source venv/bin/activate
|
||||||
|
|
||||||
|
# Install OpenClaw dependencies
|
||||||
|
echo "Installing OpenClaw dependencies..."
|
||||||
|
pip install --upgrade pip
|
||||||
|
pip install openclaw-agent
|
||||||
|
pip install pydantic fastapi uvicorn
|
||||||
|
pip install langchain langchain-community
|
||||||
|
|
||||||
|
# Configure environment variables
|
||||||
|
echo "Creating .env file..."
|
||||||
|
cat > .env << 'EOF'
|
||||||
|
# OpenClaw Configuration
|
||||||
|
OPENCLAW_API_KEY=your-api-key-here
|
||||||
|
OPENCLAW_ORCHESTRATOR_URL=http://localhost:8000
|
||||||
|
|
||||||
|
# Model Configuration
|
||||||
|
OPENAI_API_KEY=your-openai-key-here
|
||||||
|
OLLAMA_BASE_URL=http://localhost:11434
|
||||||
|
QWEN35_ENDPOINT=192.168.68.8:8080
|
||||||
|
|
||||||
|
# Agent Registry Settings
|
||||||
|
AGENT_REGISTRY_DIR=./agents
|
||||||
|
MAX_CONCURRENT_AGENTS=5
|
||||||
|
WORKFLOW_TIMEOUT=3600
|
||||||
|
EOF
|
||||||
|
|
||||||
|
# Create agents directory structure
|
||||||
|
echo "Creating agent directory structure..."
|
||||||
|
mkdir -p "$AGENT_REGISTRY_DIR"/researcher
|
||||||
|
mkdir -p "$AGENT_REGISTRY_DIR"/analyst
|
||||||
|
mkdir -p "$AGENT_REGISTRY_DIR"/writer
|
||||||
|
|
||||||
|
# Initialize git repository
|
||||||
|
echo "Initializing git repository..."
|
||||||
|
git init
|
||||||
|
git add .
|
||||||
|
git commit -m "Initial OpenClaw framework setup"
|
||||||
|
|
||||||
|
# Display configuration
|
||||||
|
echo "=== Setup Complete ==="
|
||||||
|
echo "OpenClaw installed at: $OPENCLAW_DIR"
|
||||||
|
echo "Run: source venv/bin/activate"
|
||||||
|
echo "Start orchestrator: python orchestrator.py"
|
||||||
|
echo ""
|
||||||
|
echo "Next steps:"
|
||||||
|
echo "1. Set your API keys in .env file"
|
||||||
|
echo "2. Create custom agent definitions in $AGENT_REGISTRY_DIR/"
|
||||||
|
echo "3. Test with: python test_agents.py"
|
||||||
Reference in New Issue
Block a user