AI Context Memory System

[mikejmorgan-ai]

Description:
Build intelligent memory system that learns from past installations and user patterns.

Purpose:

• Remember successful installation patterns per user/system
• Learn from errors and avoid repeating mistakes
• Suggest packages based on usage history
• Personalize AI recommendations

Requirements:

• Store installation history with context
• Track success/failure patterns
• Generate personalized suggestions
• Query interface for AI layer
• Privacy-preserving design

Example:

memory = ContextMemory()

# After successful docker install
memory.record_success(
    package='docker',
    context={'os': 'ubuntu-24.04', 'user_type': 'developer'}
)

# Later, when user asks for container tools
suggestions = memory.get_suggestions('container tools')
# Returns: ['docker', 'docker-compose', 'kubernetes']

Acceptance Criteria:

• Persistent storage of installation context
• Pattern recognition for common workflows
• Suggestion engine based on history
• Integration with LLM layer
• Privacy controls for data storage
• Tests included
• Documentation

Skills: Python, ML/AI, databases, pattern recognition

Bounty: $50 upon merge

Priority: High - Critical for AI intelligence