tao-hpu/cognitive-workspace

🧠 Active memory management system enabling functional infinite context for LLMs through cognitive workspace architecture

43
/ 100
Emerging

This project helps AI application developers build Large Language Model (LLM) applications that can remember and reason more effectively over long conversations and complex tasks. It takes your existing LLM prompt inputs and external knowledge base, then outputs more efficient and coherent responses by actively managing the LLM's memory, similar to how a human thinks. This is for developers building conversational AI, intelligent assistants, or complex reasoning agents.

Use this if you are building an LLM application that struggles with maintaining context, performing multi-step reasoning, or handling information conflicts over long interactions.

Not ideal if your LLM application primarily handles simple, single-turn queries without the need for memory or complex reasoning.

conversational-ai ai-assistant-development llm-application-architecture knowledge-retrieval multi-turn-dialogue
No Package No Dependents
Maintenance 6 / 25
Adoption 9 / 25
Maturity 15 / 25
Community 13 / 25

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95

Forks

11

Language

TeX

License

MIT

Last pushed

Nov 08, 2025

Commits (30d)

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