FRAGMENTS · ENTITIES · EPISODES
Memory Constellations
MEMORY CONSTELLATIONS · @CLARASHAFIQ
Organize scattered facts into constellations, story fragments, and long-term character understandings.
Memory charts turn specific facts in the chat into fragments, which are then organized into constellations by people, places, events, and interests, and further consolidated into readable episodes. Search using keywords, vectors, and entity aggregations simultaneously.
Project address (can be copied to AI):https://github.com/ClaraShafiq/MemoryConstellations
PROJECT INTRO
Project introduction
Memory Star Map consists of three pipelines: Scribe, Archivist and Librarian: first extract short facts from new conversations, then connect relevant facts to people, places, events and interests, and finally merge them into narrative episodes, and retrieve them across layers during chat. Each memory retains a reference to the original message.
The visualization page displays entities as constellations and bridges, while maintaining the user's recent status, long-term behavioral patterns, and the partner's own identity profile. It is suitable for long-term companion systems that are willing to host, configure personalities and pay a small amount of background model call costs.
- Suitable for:People who hope that memories can be automatically organized into long-term narratives and retain evidence chains and user models.
- Platform:Self-hosted web service, requires Node.js, SQLite, ChromaDB and at least one model API.
- Usage:Fill in the user, AI and relationship configuration, start the memory pipeline, and then connect the search results to the chat prompt.
- License:MIT。
COMMENTS & FEEDBACK
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