What is Memory
What is Memory in TorqAgent?
Memory in TorqAgent is a feature that enables the AI to remember previous conversations. It does this by storing conversations in arrays or databases, providing them as context to the Large Language Model (LLM). This way, the AI can refer back to earlier parts of the conversation, making interactions more coherent and contextually relevant.
How Does Short Term Memory Work in TorqAgent?
Short Term Memory in TorqAgent is designed for temporary storage of past conversations in RAM. It stores these interactions in an array format. However, this data is ephemeral and will be lost when the TorqAgent instance is restarted. There are three types of short-term memory nodes: BufferMemory, BufferWindowMemory, and ConversationSummaryMemory, each serving different purposes in conversation management.
What is Long Term Memory in TorqAgent and How Does it Function?
Long Term Memory in TorqAgent refers to memory nodes capable of persisting past conversations over time. This feature is particularly useful for resuming conversations and keeping track of interactions for different users. Long Term Memory achieves this by using various database integrations like DynamoDB Chat Memory, Motorhead Memory, Redis Chat Memory, etc. It also enables separate conversations for multiple users through unique session IDs.
Memory in TorqAgent is a feature that enables the AI to remember previous conversations. It does this by storing conversations in arrays or databases, providing them as context to the Large Language Model (LLM). This way, the AI can refer back to earlier parts of the conversation, making interactions more coherent and contextually relevant.
How Does Short Term Memory Work in TorqAgent?
Short Term Memory in TorqAgent is designed for temporary storage of past conversations in RAM. It stores these interactions in an array format. However, this data is ephemeral and will be lost when the TorqAgent instance is restarted. There are three types of short-term memory nodes: BufferMemory, BufferWindowMemory, and ConversationSummaryMemory, each serving different purposes in conversation management.
What is Long Term Memory in TorqAgent and How Does it Function?
Long Term Memory in TorqAgent refers to memory nodes capable of persisting past conversations over time. This feature is particularly useful for resuming conversations and keeping track of interactions for different users. Long Term Memory achieves this by using various database integrations like DynamoDB Chat Memory, Motorhead Memory, Redis Chat Memory, etc. It also enables separate conversations for multiple users through unique session IDs.
Updated on: 04/04/2024
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