Скачать или смотреть AnythingLLM Tutorial: Scrape & Chat with ANY Website! (Elementor RAG Demo)

✨ Effortlessly transform any website's content into a powerful, queryable AI knowledge base using AnythingLLM! In this step-by-step tutorial, I'll show you how to scrape the Elementor help documentation, embed it into a LanceDB vector store, and chat with your custom RAG system.

🚀 *What you'll see in this video:*
We dive into creating a custom workspace in AnythingLLM, focusing on ingesting data from the Elementor help site using the built-in Bulk Link Scraper. I'll walk you through configuring the scraper, monitoring the process with Coolify Docker logs, and then adding these documents to your workspace for embedding into the LanceDB vector database. Finally, we'll test our new Elementor knowledge base by asking questions directly in the chat interface!

💡 *Discover & Learn:*
🔹 How to set up and use AnythingLLM's Data Connectors (Bulk Link Scraper).
🔹 Understanding crawl depth and page limits for effective web scraping.
🔹 The importance of monitoring background processes like scraping and embedding (using Coolify).
🔹 The document chunking and vectorization process for RAG.
🔹 Configuring LLM providers (like Google Gemini) within AnythingLLM.
🔹 An overview of AnythingLLM's workspace settings: General, Chat, Vector Database, and Agent Configuration.
🔹 The power of RAG for creating custom AI assistants.

🛠️ *Tools & Resources Mentioned:*
AnythingLLM (Self-Hosted Docker Version)
Coolify (Docker Management)
LanceDB (Vector Database)
Elementor Help Website: `https://elementor.com/help/`
Google Gemini

🔗 *Useful Links:*
AnythingLLM: `https://anythingllm.com/`
Coolify: `https://coolify.io/`
LanceDB: `https://lancedb.com/`
Elementor: `https://elementor.com/`

⏰ *Timestamps:*
00:00 - Intro: AnythingLLM for Custom Workspaces
00:13 - Configuring the Bulk Link Scraper for Elementor Docs
01:00 - Setting Crawl Depth (2) & Max Pages (200)
01:20 - Monitoring Scraper with Coolify Docker Logs
01:56 - Understanding LanceDB: The Vector Database
02:59 - Live Scraping: Watching the Logs
04:14 - Deep Dive: AnythingLLM Workspace Settings (General & Chat)
04:54 - LLM Provider Options (OpenAI, Gemini, Anthropic & more)
05:23 - Agent Configuration & Skills Overview
05:59 - Vector Database Settings Explained
06:30 - Scraping Complete: Adding Documents to Workspace
07:02 - Embedding Process: Chunking & Vectorizing into LanceDB
09:30 - Checking Vector Count in Database
09:41 - Querying Your New Elementor Knowledge Base!
10:00 - Reviewing Chat Response & Source Citations

💬 Have you tried AnythingLLM or building your own RAG system? What are your favorite use cases? Let me know in the comments! 👇
👍 If this video helped you, please give it a thumbs up and 🔔 subscribe for more AI and tech tutorials!

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