Building Chatbot Apps with Flowise: FAQ scraping and embedded chatbot

This video is about building a chatbot that understands FAQs and can answer questions in a natural language way.

The process is divided into three parts: collecting information from a website, creating a flow, and embedding the flow into a website.

The video demonstrates how to automatically collect information from a website and use it to create a chatbot.

💡 Learn how to use Flowise to create ChatGPT AI apps visually.

🔑 Add necessary API keys, namespaces, and index to store and retrieve information.

🕸️ Configure web scraping settings to crawl multiple levels of a website.

💬 Implement a conversational retrieval QA chain to interact with the user using a language model.

🔍 The AI scrapes a website to populate a vector store with information.

💡 After populating the vector store, the AI can answer questions based on the website information.

✅ The AI successfully extracts and summarizes information about ratings, cost estimates, and tipping for a ride-sharing service.

📄 The video demonstrates how to build a flow using Flowise to query website data.

🔁 The flow starts with an upsert operation and then duplicates the chat flow for querying purposes.

🔑 API keys and the region are added to the flow to access and retrieve data from the vector store.

👉 You can control the number of vectors returned in the query result.

✨ Learn how to embed collected FAQ information into a website chat widget.

🔧 Customize the appearance and functionality of the embedded chat widget.

💡 By adding code to the HTML file, a custom button is inserted into the web page, allowing users to interact with a chatbot.

🌈 The chat flow can be customized by changing the background color, button placement, size, and custom icon.

🤖 The welcome message, avatar/profile picture for both the bot and user, and text input placeholder can also be customized.

📱 Customizations options are available when embedding the chat flow into a website.

🔄 Modifications to the flow logic will automatically update the embedded chat bubble.

💡 The chat flow can display additional information and sources of collected information.