Developer Builds Offline AI Companion With Local Memory That Never Leaves Your Device

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A developer building a desktop AI companion called Local Waifu set a strict rule that all conversations and memories must remain stored on the user's own machine, with no server required. To solve the problem of meaningful recall, the project separates short-term chat history from long-term memory, storing both in a local SQLite database unique to each character. Each memory entry includes metadata such as importance, emotional weight, recency, and a 768-dimensional vector embedding that enables semantic search entirely on-device. At recall time, the system ranks relevant memories using a weighted combination of vector similarity, recency, and emotional significance rather than relying on exact keyword matches. The approach ensures that personal conversation data never leaves the user's computer while still allowing the AI to surface contextually relevant details from past interactions.

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