video1.0<iframe src="https://www.loom.com/embed/b8fb9b43f9b6431290239ed10bb880fc" frameborder="0" width="1728" height="1296" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12961728Loomhttps://www.loom.com12961728https://cdn.loom.com/sessions/thumbnails/b8fb9b43f9b6431290239ed10bb880fc-1718893575449.gif219.167Hey community, it's Vladimir here 🤩 I'm excited to share an update on our project, nowWiki 🤔 We're working on integrating a private Large Language Model (LLM) to create an automated support agent on our website 🤖 🤝 The idea is to have a chatbot that can answer questions, provide data, and even create summaries 📊 We're considering two options: DBGPT and private GPT 🤔 🔍 DBGPT taps into databases and can generate questions and answers, act as a chat agent, render data, and create summaries 📊 It's like having a super smart assistant 🤖 📊 Private GPT vectorizes documents and allows querying via API or widget 📊 It supports OpenAI API standards and has other cool features 🤩 🤝 Both options look very attractive for our knowledge database 📚 We're excited to explore these solutions and bring them to life 🎉 👀 What do you think? Are you as excited as I am? Let's discuss this further in the comments below 💬