Aurelis

Aurelis Interactive Shell Guide

Complete guide to the enterprise-grade interactive development environment

🚀 Overview

The Aurelis Interactive Shell is a powerful, AI-powered development environment that provides real-time access to GitHub’s cutting-edge AI models for code analysis, generation, and optimization. It combines the convenience of a command-line interface with the intelligence of modern AI systems.

🎯 Key Features

✨ Core Capabilities

• 17 Production-Ready Commands for comprehensive development workflows
• Real-time AI Integration with 9 GitHub models via Azure AI Inference
• Intelligent Auto-completion for commands, files, and context-aware suggestions
• Rich Interactive Interface with syntax highlighting and progress indicators
• Session Management with persistent history and state tracking
• Multi-language Support for Python, JavaScript, TypeScript, Java, C++, and more

🔧 Enterprise Features

• Audit Logging for compliance and tracking
• Security Controls with file filtering and access management
• Performance Optimization with caching and concurrent request handling
• Error Recovery with graceful degradation and fallback systems

🚀 Getting Started

Starting the Shell

# Start interactive shell
aurelis shell

# Start with specific configuration
aurelis shell --config /path/to/config.yaml

# Start in debug mode
aurelis shell --debug

First-Time Setup Verification

# Check system status
aurelis:project> status

# Verify GitHub models
aurelis:project> models

# Test AI functionality
aurelis:project> generate "simple hello world function"

📋 Command Reference

🆘 Help & Navigation

help - Get Command Information

# Show all available commands
aurelis:project> help

# Get detailed help for specific command
aurelis:project> help analyze
aurelis:project> help generate
aurelis:project> help search

status - System Status Check

# Show comprehensive system status
aurelis:project> status

# Example output:
# ┌─────────────────────┬─────────────┬─────────────────────┐
# │ Component           │ Status      │ Details             │
# ├─────────────────────┼─────────────┼─────────────────────┤
# │ Session Manager     │ ✓ Active    │                     │
# │ Model Orchestrator  │ ✓ Active    │ 9 models available  │
# │ Code Analyzer       │ ✓ Active    │                     │
# └─────────────────────┴─────────────┴─────────────────────┘

🔍 Code Analysis & Search

analyze - Comprehensive Code Analysis

# Analyze a specific file
aurelis:project> analyze src/main.py

# Example output with metrics:
# ┌─────────────────┬─────────────┐
# │ Metric          │ Value       │
# ├─────────────────┼─────────────┤
# │ Lines of Code   │ 245         │
# │ File Size       │ 8,432 bytes │
# │ Language        │ python      │
# │ Complexity      │ Medium      │
# └─────────────────┴─────────────┘

search - Intelligent Codebase Search

# Search for code patterns
aurelis:project> search "function definition"
aurelis:project> search "import pandas"
aurelis:project> search "class"

# Example output with highlighted matches:
# File: src/utils/helpers.py
#   42: def process_data(input_data):
#   58: def validate_input(data):
# 
# File: src/models/analyzer.py
#   15: def analyze_code(content):
#   89: def generate_report():

🤖 AI-Powered Development

generate - AI Code Generation

# Generate code from natural language
aurelis:project> generate "REST API endpoint for user authentication"
aurelius:project> generate "Python function to parse CSV files"
aurelis:project> generate "React component for file upload"

# The AI will generate complete, production-ready code with:
# - Proper error handling
# - Documentation
# - Type hints (where applicable)
# - Best practices implementation

explain - Code Explanation

# Get detailed explanation of code
aurelis:project> explain src/complex_algorithm.py

# Example output:
# ╭─ Code Explanation: complex_algorithm.py ─╮
# │                                          │
# │ ## Purpose                               │
# │ This module implements a sophisticated   │
# │ sorting algorithm with O(n log n)        │
# │ complexity...                            │
# │                                          │
# │ ## Key Components                        │
# │ - quicksort(): Main sorting function     │
# │ - partition(): Helper for pivot          │
# │ - median_of_three(): Optimization       │
# ╰──────────────────────────────────────────╯

docs - AI Documentation Generation

# Generate comprehensive documentation
aurelis:project> docs src/api/endpoints.py

# Generates professional documentation including:
# - Function/class descriptions
# - Parameter documentation  
# - Return value specifications
# - Usage examples
# - Error handling information

# Option to save to file:
# Save documentation to file? [y/N]: y
# Enter filename [generated_docs.md]: api_documentation.md
# ✓ Documentation saved to api_documentation.md

fix - Automated Code Fixing

# Analyze and fix code issues
aurelis:project> fix src/buggy_code.py

# AI will identify and suggest fixes for:
# - Syntax errors
# - Logic issues
# - Performance problems
# - Security vulnerabilities
# - Code style violations

refactor - Intelligent Refactoring

# Get refactoring suggestions
aurelis:project> refactor src/legacy_code.py

# AI provides suggestions for:
# - Code structure improvements
# - Performance optimizations
# - Readability enhancements
# - Design pattern applications
# - Maintainability improvements

test - Test Generation

# Generate comprehensive tests
aurelis:project> test src/calculator.py

# AI generates:
# - Unit tests with multiple scenarios
# - Edge case testing
# - Mock implementations
# - Test data fixtures
# - Performance benchmarks

🎛️ Configuration & Management

config - Configuration Management

# Show current configuration
aurelis:project> config

# Show specific configuration section
aurelis:project> config models
aurelis:project> config security

# Modify configuration
aurelis:project> config set models.primary gpt-4o
aurelis:project> config set cache.ttl 7200

models - AI Model Management

# List available GitHub models
aurelis:project> models

# Example output:
# ┌─────────────────────┬──────────┬─────────────────────────────┐
# │ Model               │ Provider │ Best For                    │
# ├─────────────────────┼──────────┼─────────────────────────────┤
# │ codestral-2501      │ Mistral  │ Code generation             │
# │ gpt-4o              │ OpenAI   │ Complex reasoning           │
# │ gpt-4o-mini         │ OpenAI   │ Fast responses              │
# │ cohere-command-r    │ Cohere   │ Documentation               │
# └─────────────────────┴──────────┴─────────────────────────────┘

# Test model connectivity
aurelis:project> models health

# Switch primary model
aurelis:project> models switch gpt-4o

session - Session Management

# Show current session information
aurelis:project> session

# List all available sessions
aurelis:project> session list

# Session management operations
aurelis:project> session save current_work
aurelis:project> session load previous_session
aurelis:project> session clear
aurelis:project> session export session_backup.json

tools - Available Tools

# List registered development tools
aurelis:project> tools

# Example output:
# ┌──────────────────┬─────────────────────────────────────┬────────┐
# │ Tool             │ Description                         │ Status │
# ├──────────────────┼─────────────────────────────────────┼────────┤
# │ Code Analyzer    │ Static analysis and quality check   │ Active │
# │ Model Router     │ AI model routing and management     │ Active │
# │ Session Manager  │ Development session persistence     │ Active │
# │ Context Manager  │ Code context and file tracking      │ Active │
# └──────────────────┴─────────────────────────────────────┴────────┘

🛠️ Utility Commands

history - Command History

# Show recent command history
aurelis:project> history

# Example output:
# ┌───────┬─────────────────────────────────────┐
# │ Index │ Command                             │
# ├───────┼─────────────────────────────────────┤
# │   1   │ analyze src/main.py                 │
# │   2   │ generate "API endpoint"             │
# │   3   │ search "function"                   │
# │   4   │ docs src/utils.py                   │
# └───────┴─────────────────────────────────────┘

clear - Clear Screen

# Clear screen and redisplay welcome
aurelis:project> clear

exit / quit - Exit Shell

# Exit shell with session saving
aurelis:project> exit
aurelis:project> quit

# Output:
# Saving session...
# ✓ Session saved successfully
# Goodbye!

🎨 Shell Features

Auto-completion

The shell provides intelligent auto-completion for:

# Command completion
aurelis:project> gen<TAB>
generate

# File path completion  
aurelis:project> analyze src/<TAB>
src/main.py    src/utils.py    src/config.py

# Context-aware completion
aurelis:project> config <TAB>
show    set    get    models    cache    security

aurelis:project> session <TAB>
list    load    save    clear    info    export    import

Syntax Highlighting

• Commands appear in cyan
• File paths appear in blue
• Success messages appear in green
• Error messages appear in red
• Code blocks have language-specific highlighting

Progress Indicators

Long-running operations show progress:

aurelis:project> generate "complex algorithm"
⠋ Generating code... 

aurelius:project> search "large codebase query"
⠙ Searching... [████████████████████████████████] 1,247 files scanned

Rich Output Formatting

Results are displayed in professional tables and panels:

# Tables for structured data
┌─────────────────┬─────────────┐
│ Metric          │ Value       │
├─────────────────┼─────────────┤
│ Lines of Code   │ 1,247       │
└─────────────────┴─────────────┘

# Panels for detailed information
╭─ Generated Code ─╮
│                  │
│ def authenticate │
│   # Complete     │
│   # implementation
╰──────────────────╯

# Syntax-highlighted code blocks
import pandas as pd
import numpy as np

def process_data(df: pd.DataFrame) -> pd.DataFrame:
    """Process the input dataframe."""
    return df.dropna()

🔧 Advanced Usage

Workflow Integration

Development Workflow Example

# 1. Start new development session
aurelis:project> session clear

# 2. Analyze existing codebase
aurelis:project> search "TODO"
aurelis:project> analyze src/main.py

# 3. Generate new functionality
aurelis:project> generate "user authentication middleware"

# 4. Create documentation
aurelis:project> docs src/auth/middleware.py

# 5. Generate tests
aurelis:project> test src/auth/middleware.py

# 6. Save session for later
aurelis:project> session save auth_implementation

Code Review Workflow

# 1. Analyze code quality
aurelis:project> analyze src/new_feature.py

# 2. Get refactoring suggestions
aurelis:project> refactor src/new_feature.py

# 3. Identify potential issues
aurelis:project> fix src/new_feature.py

# 4. Generate comprehensive documentation
aurelis:project> docs src/new_feature.py

# 5. Create test coverage
aurelis:project> test src/new_feature.py

Batch Operations

# Search and analyze multiple files
aurelis:project> search "deprecated"
# Then analyze each file found:
aurelis:project> analyze src/legacy/old_api.py
aurelis:project> refactor src/legacy/old_api.py

# Generate documentation for entire module
aurelis:project> docs src/api/
aurelius:project> docs src/models/
aurelis:project> docs src/utils/

Session Management Best Practices

# Create themed sessions for different work
aurelis:project> session save frontend_work
aurelis:project> session save backend_api
aurelis:project> session save testing_suite

# Export sessions for backup
aurelis:project> session export frontend_backup.json

# Load specific session for context
aurelis:project> session load backend_api

🛡️ Security & Compliance

Secure File Handling

# The shell automatically filters sensitive files
aurelis:project> analyze config/secrets.yaml
# ❌ Access denied: File contains sensitive information

# Safe file patterns are allowed
aurelius:project> analyze src/main.py
# ✓ Analysis complete

# Check security settings
aurelis:project> config security

Audit Trail

# All commands are logged for audit purposes
aurelis:project> analyze src/financial_data.py
# Logged: User analyzed financial_data.py at 2025-06-17 14:30:00

# Session activities are tracked
aurelis:project> session info
# Session ID: abc123-def456
# Commands executed: 15
# Files accessed: 8
# Start time: 2025-06-17 14:00:00

🚨 Troubleshooting

Common Issues

1. AI Model Connectivity

# Check model status
aurelis:project> models health

# If models are unavailable:
# ❌ Model connectivity issue: Check GitHub token

# Test GitHub token
aurelis:project> config test

2. File Access Issues

# If file cannot be accessed:
aurelis:project> analyze /restricted/file.py
# ❌ File not found or access denied

# Check current directory
aurelis:project> pwd
# Check file permissions and paths

3. Performance Issues

# Check current configuration
aurelis:project> config processing

# Adjust concurrent requests if needed
aurelis:project> config set processing.concurrent_requests 3

# Clear cache if needed
aurelis:project> config set cache.enabled false

4. Session Issues

# If session fails to save:
aurelis:project> session clear
aurelis:project> session save new_session

# Check session directory permissions
aurelis:project> config show | grep session

📊 Performance Tips

Optimization Strategies

1. Use specific commands instead of general analysis for better performance
2. Enable caching for frequently accessed operations
3. Limit concurrent requests based on your API quotas
4. Use appropriate models for different tasks (e.g., gpt-4o-mini for quick responses)

Recommended Workflows

1. Start with search to understand codebase structure
2. Use analyze for specific files rather than entire directories
3. Generate documentation incrementally rather than all at once
4. Save sessions to preserve context between work periods

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🎯 Next Steps:

• GitHub Models Integration - Deep dive into AI capabilities
• Best Practices - Optimize your workflow
• CLI Reference - Learn command-line usage
• Enterprise Features - Explore advanced capabilities