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#ai-chatbot At my last company, I built a chatbot that reco

4 steps

  1. 1

    2026년 10월 5일

    Key features: - 3-way hybrid search: mood, specs and keywords - An LLM reads each question first, pulls out filters (category, color, budget) and asks back if it's vague - Filters run inside the DB, so jeans never return a jacket - Ranking boost for popular items and our own brand - Reviews summarized by AI and searched as specs

  2. 2

    2026년 10월 5일

    The new data needed changes: - Korean values became English, prices became USD - Amazon has no clean color/material/season fields, so I extract them from product text And for a portfolio: - Balanced picks across categories, with Amazon's own brands standing in as "our brand" - A live monitoring page that shows every reasoning step - Rate limits to cap API costs

  3. 3

    2026년 10월 5일

    Next up: - Security fixes before going public (admin API auth, input length limits) - Deploying on a free server so anyone can try it 🔗 github.com/summerr0-0/chatbot_project

  4. 4

    2026년 10월 6일

    #aichatbot At my last company, I built a chatbot that recommended products from our online fashion store (Gemini + Milvus RAG)It ran on our in-house data: product info like category, color, material and season, plus customer reviews and sales numbers.After I left, I couldn't use that data anymore, so I rebuilt it on Amazon's public review dataset (8,500 clothing items).

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