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:
2026-05-07 11:40:02 +00:00
parent d47dc23b81
commit 05eccd5b53
51 changed files with 1690 additions and 1476 deletions
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#!/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 $EDUCATION_DIR/curriculum/"
echo ""
echo "Perfect for Jerome and Theodore's strategy sessions on AI agent frameworks!"
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#!/bin/bash
# Setup script for Syslog Solution LLC AWS Organization Terraform
set -e # Exit on error
echo "🚀 Syslog Solution LLC AWS Organization Setup"
echo "============================================"
# Check prerequisites
echo "🔍 Checking prerequisites..."
# Check AWS CLI
if ! command -v aws &> /dev/null; then
echo "❌ AWS CLI not found. Please install AWS CLI first."
echo " Visit: https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html"
exit 1
fi
# Check Terraform
if ! command -v terraform &> /dev/null; then
echo "❌ Terraform not found. Please install Terraform first."
echo " Visit: https://developer.hashicorp.com/terraform/tutorials/aws-get-started/install-cli"
exit 1
fi
echo "✅ Prerequisites check passed"
# Configure AWS CLI
echo ""
echo "🔧 Configuring AWS CLI..."
echo "Please enter your AWS credentials for the new business account:"
read -p "AWS Access Key ID: " AWS_ACCESS_KEY_ID
read -p "AWS Secret Access Key: " AWS_SECRET_ACCESS_KEY
aws configure set aws_access_key_id "$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 "============================================"
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#!/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"