Advanced RAG with LlamaIndex - Metadata Extraction [2025]
Learn advanced Retrieval-Augmented Generation (RAG), focusing on techniques such as metadata augmentation and metadata filtering using LlamaIndex. This will help you improve your RAG models for better performance and accuracy.
Links
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Notebook: https://colab.research.google.com/gis...
AI Engineering Bootcamp (join the waitlist): http://aibootcamp.dev/
Buy me a coffee (or a beer): https://buymeacoffee.com/alejandro.ao
What You'll Learn
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Advanced RAG Techniques: Understand the intricacies of Retrieval-Augmented Generation and how it can boost your AI models.
Metadata Augmentation: Learn how to enrich your data with metadata to improve retrieval and generation processes. Also, control what metadata is sent to your LLM and embedding model.
Hands-On Notebook: Follow along as we explore a detailed Jupyter notebook, showcasing practical applications of these techniques.
LlamaIndex Integration: See how LlamaIndex can be integrated into your workflow to streamline RAG processes.
Timestamps
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0:00 Intro
2:21 Quick Explanation of RAG
6:21 Setup
7:07 Extract text from File
12:26 Metadata Selection
22:40 Metadata Extraction
35:46 Create An Index
43:55 Use a Vector Store
50:15 Conclusion
