HomeCache: What If Your Home Could Actually Remember?

说明与用途

HomeCache 通过 RAG 架构存储和检索家庭文件信息，使用户能够使用自然语言查询并获得带来源信息的答案。

问题

Household information is scattered across invoices, warranties, receipts, and manuals, making it hard to recall where specific details are stored.

结果

HomeCache enables quick, trustworthy answers to household queries by leveraging user-uploaded documents and a RAG architecture.

工作流

• Upload household documents
• Text extraction and chunking
• Generate embeddings for chunks
• Store chunks and embeddings in MongoDB Atlas Vector Search
• Ask a question in natural language
• Convert question to embedding
• Retrieve relevant memory chunks
• Feed question + memories to Gemma-2-2B-IT
• Generate grounded answer with source attribution
• Display answer and supporting document

证据

I built HomeCache, an AI-powered memory for your home.

来源

You can upload your household documents, and instead of digging through files one by one, you can simply ask questions about them in natural language.

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HomeCache reads and processes it, breaks the information into smaller searchable pieces, and stores those memories in a vector database.

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The relevant memories are then passed to Gemma-2-2B-IT, an open-weight model from Google.

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HomeCache also keeps track of which documents were used to answer a question.

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