Скачать или смотреть RAG System Demo: Preventing LLM Hallucination with Vector Databases & Gemini 2.0 Flash

This video demonstrates a Retrieval-Augmented Generation (RAG) system using Google Cloud tools, showing how it prevents LLM hallucination [i, j]. It builds a context database from a YouTube video and follows five main steps:

Download the video (MP4).

Convert it to MP3 audio.

Transcribe the audio via Google Cloud Speech-to-Text; store text in Cloud Storage.

Generate embeddings from transcript chunks using Vertex AI and store in a vector database.

Query the database via Vertex AI and feed retrieved chunks to Gemini 2.0 Flash.

The demo highlights that the LLM strictly uses stored context, even if factually unusual:

"Australians eat breakfast" → spaghetti or sushi.

"Language Australians speak" → formal French.

"What Australians love" → winter snow festivals.

The video shows RAG is ideal for large datasets, helping teachers turn videos into notes and YouTubers/marketers reuse content for blogs or summaries [i].