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In this video, we explore how to set up and run LightRAG—a retrieval augmented generation (RAG) system that combines knowledge graphs with embedding-based retrieval—locally using OLLAMA. This video provides a step-by-step guide on cloning the repo, configuring local models like the Qwen2 LLM, adjusting context windows, and visualizing knowledge graphs generated from example data such as “A Christmas Carol” by Charles Dickens.
LINKS:
https://github.com/HKUDS/LightRAG
https://lightrag.github.io/
https://arxiv.org/pdf/2410.05779
https://microsoft.github.io/graphrag/
https://youtu.be/vX3A96_F3FU
💻 RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag
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TIMESTAMP
00:00 LightRAG with local models
01:38 Setup with Ollama
02:53 Serving Embeddings with Ollama
03:40 Changing the context window of the LLM
07:00 Configuring the Ingestion process
08:12 Advanced RAG Course
09:14 Indexing and Knowledge Graph Creation
10:45 Testing it out with local models
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