Developed in just 4.5 months, VAC Memory System is for conversational memory in LLM agents, achieving state-of-the-art accuracy of 80.1% on the LoCoMo benchmark. Its proprietary MCA ranking ensures efficient performance and cost-effectiveness.
Transforming the Journey from Cell Tower Climber to SOTA AI Memory in Just 4.5 Months
The world's most accurate open-source conversational memory for LLM (Large Language Model) agents
The VAC Memory System represents the pinnacle of advancements in conversational memory, achieving an impressive 80.1% accuracy on the LoCoMo benchmark. Created with a commitment , this system is engineered for versatility and performance, providing a robust solution for developers and businesses alike.
The architecture of the VAC Memory System is designed for efficiency and accuracy. It employs a hybrid retrieval mechanism integrating:
To illustrate the system's setup, here’s a quick code snippet for initiating tests:
git clone https://github.com/vac-architector/VAC-Memory-System.git
cd VAC-Memory-System
export OPENAI_API_KEY="your_api_key"
./run_test.sh
The VAC Memory System not only exemplifies technological innovation but also democratizes AI memory, allowing small players to compete alongside bigger corporations. The open-source nature fosters collaboration and encourages continuous advancements in AI memory technologies.
This project welcomes various partnerships:
The VAC Memory System stands as a testament to what is achievable with determination, showcasing that significant milestones can be reached from unexpected beginnings. Open to collaboration and exploration, it aims to innovate and improve the landscape of AI memory continuously.
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