Complete program for structured management of dialogue
Core is designed specifically to address this issue and is implemented at three levels:
- Basic Configuration: When creating conversation rules in Settings, be sure to set a unique sessionId (UUID generator is recommended) so that you can string together a single complete conversation.
- Storage OptimizationFor long conversations, it is recommended to enable the "chunk storage" function, which generates a child node for every 5 rounds of conversation to avoid too large memory nodes.
- Analytical Applications: Using the clustering view on the Graph page, the system automatically categorizes conversations by time/topic, and clicking on a node allows you to see the specific prompt and response content
Note: The current Llama model requires additional middleware configuration to convert the data format, so it is recommended to use the GPT series model for the time being for best compatibility.
This answer comes from the articleCore: a tool for personalized memory storage for large modelsThe
May not be reproduced without permission:AI productivity tools " How to solve the pain point of large model conversation logs that are difficult to manage in a structured way?
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