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docs: add recommender system example (#1561)

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Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
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Rithik Kumar
2024-08-25 12:30:30 +05:30
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docs/src/examples/python_examples/rag.md
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**RAG: Revolutionize Information Retrieval with LanceDB 🔓🧐**
====================================================================
Unlock the full potential of Retrieval-Augmented Generation (RAG) with LanceDB, a solution for efficient vector-based information retrieval 📊.
Build RAG (Retrieval-Augmented Generation) with LanceDB, a powerful solution for efficient vector-based information retrieval 📊.
**Experience the Future of Search 🔄**
RAG integrates large language models (LLMs) with scalable knowledge bases, enabling efficient information retrieval and answer generation 🤖. By applying RAG to industry-specific use cases, developers can optimize query processing 📊, reduce response latency ⏱️, and improve resource utilization 💻. LanceDB provides a robust framework for integrating LLMs with external knowledge sources, facilitating accurate and informative responses 📝.
🤖 RAG enables AI to **retrieve** relevant information from external sources and use it to **generate** more accurate and context-specific responses. 💻 LanceDB provides a robust framework for integrating LLMs with external knowledge sources 📝.
| **RAG** | **Description** | **Links** |
|----------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|