Memoripy
AI memory layer for smarter agents
Memoripy launched on November 23, 2024 with 15 votes, #990 of 4,990 launches that month and more than 50% of that year's launches. The site was not reachable when checked in September 2026.
What it does
An AI memory layer with short- and long-term storage, semantic clustering, and optional memory decay for context-aware applications.
Does a similar job
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Memoripy – AI Memory Layer with Short- & Long-Term Memory, Clustering2024 · github.com · ▲7Hey HN! I built Memoripy, a memory layer for AI that adds short-term, long-term, and semantic memory capabilities to enhance LLM applications. It helps AI systems retain and prioritize past interactions, adapt over time, and respond with greater context and personalization. Memoripy uses semantic clustering to retrieve relevant memories, along with adaptive memory decay and reinforcement, so interactions stay fresh and context-aware. It’s designed for easy integration with OpenAI, Ollama, and other platforms—giving your AI applications dynamic memory management with minimal setup. Would love…
YourMemoryApr 2026 · yourmemoryai.vercel.app · ▲93This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…
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