A practical approach to building an effective long-term memory system
VirtualWife uses short-term dialog memory by default, to achieve deep memory you need to go through the following steps:
- Memory Storage Configuration::
- exist
.envAddMEMORY_TYPE=json(default use of memory vulnerable to loss) - indicate clearly and with certainty
MEMORY_FILE_PATH=./memory.jsonImplementing Disk Persistence
- exist
- Key information extraction::
- Model conversation format: "[Memory] My birthday is June 15" (the system automatically flags key information)
- Add memorized prompts to the role setting template to require the AI to actively ask for user preferences
- Regular memory reinforcement::
- After every 20 conversations, the system will automatically repeat the 5 key messages previously recorded to confirm the
- utilization
curl -X POST http://localhost/memory/refreshManually triggered memory reorganization
Advanced Programs:
Connection to external databases for structured memory:
- modifications
docker-compose.ymlAdding a PostgreSQL Container - set up
MEMORY_TYPE=postgresand configure the connection parameters - Memory data will be categorized and stored by timestamp to support complex queries
This answer comes from the articleVirtualWife: A secondary digital person that supports B-station live streaming and voice interactionThe
May not be reproduced without permission:AI productivity tools " How to implement VirtualWife's long-term memory function for user preferences?
