CC

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Large Language Models often struggle with "intent forgetting" during extended conversations, losing track of initial goals, constraints, and past decisions, leading to inconsistent responses. CC offers a revolutionary solution by providing intelligent context management. It employs a hierarchical context architecture, intelligent intent classification, and robust context management to ensure LLM-powered AI agents maintain conversational consistency, remember crucial details, and deliver relevant responses even after numerous turns, enhancing the effectiveness of long-term AI interactions.

Características Principales

• Hierarchical Context Architecture for long, mid, and short-term memory
• Intelligent Intent Classification to categorize user messages (e.g., PROBLEM_DEFINITION, CONSTRAINT_ADDITION)
• Intelligent Context Management that automatically organizes and prunes context
• High Performance with sub-0.3s average response times and multi-session scalability
• Multi-Session Support for managing concurrent AI conversations
• 2 GitHub stars

Casos de Uso

• Preventing LLMs from losing context or 'intent forgetting' in extended conversations
• Maintaining awareness of core problems and objectives throughout multi-turn AI interactions
• Ensuring LLM responses consistently apply accumulated constraints and decisions