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Give AI agents decaying memory storage, retrieval, and permanent journal verification.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "memory-decay" yet — see the docs or source repo.
Integrate memory-decay into my AI assistant: let short-term preferences and context decay over time, keep recently accessed information longer, and write key decisions to the permanent journal. Provide example flows for memory write, read, and verification.
A setup plan showing how to manage decaying memory, preserve important records, and handle typical calls.
I want the agent to revisit past memories about user requirements, but only trust content that can be verified in the permanent journal. Design a retrieval strategy: read related memories first, then check the journal, and finally rank results by confidence.
A retrieval strategy with verification steps to distinguish faded memories from verifiable facts.
Use memory-decay to design memory rules for a long-running research agent: let temporary clues decay automatically, extend retention for repeatedly used knowledge, write milestone conclusions to the permanent journal, and explain suitable parameters and maintenance tips.
A memory strategy for long-running tasks, including decay rules, retention conditions, and permanent logging advice.
Give AI agents a memory layer with storage, recall, forgetting, and reinforcement.
Give AI assistants persistent memory, adaptive recall, and graph-based knowledge retrieval.
Give AI agents persistent memory and semantic retrieval across conversations.
Give AI agents local persistent memory with hybrid search and decay management.
Give AI agents persistent semantic memory with search, decay, and deduplication.
Give AI agents persistent memory with semantic search for knowledge and reflections.