Use this Advanced RAG Trick to Boost Retrieval Performance
Hi, My name is Sunny Solanki, and in this video, I provide a step-by-step guide to implementing the Advanced RAG algorithm Query Expansion (Hypothetical Document Embedding). For explaining the algorithm through examples, we use open-source LLM Llama-3.1 (70B) freely available through Groq API. For storing tutorial docs, we use open source vector database Chroma.
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CODE - https://github.com/sunny2309/advanced...
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Important Chapters:
0:00 - Query Expansion Intro
0:35 - Concept Explanation
1:58 - Code Start
5:43 - Load Data (PDF Document)
7:57 - Add Data to Vector Store
12:51 - Search Vector Store using Query
15:45 - Query Expansion with Generated Answer
18:07 - Visualize Query Expansion Retrieval Results
19:03 - Query Expansion with Generated Queries
23:06 - Visualize Query Expansion Retrieval Results
24:48 - Build RAG to Check Retrieval Performance of Query Expansion
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