Context-Aware AI agent: Memory Management and state Tracking

Context awareness has become a crucial feature that distinguishes sophisticated systems from basic chatbots. This article I will guide you through creating a context-aware AI agent using Large Language Models (LLMs), combining theoretical understanding with practical pseudocode implementation.

Understanding Context Awareness

Let me give you some context about about what I meant about context awareness in AI agents. Context awareness mainly refers to the Agent’s ability to:

• Maintain conversation history
• Remember user preferences (e.g., likes, dislikes, event etc)
• Understand temporal and situational events
• Track and update conversation state
• Handle context switches gracefully

The following illustration shows the visual representation of how context flows in an AI agent:

The above diagram shows the flow of context in an AI agent system. The user input is processed by the NLU agent, which then interacts with the context manager, memory system, and state…