Build Your Own RAG App: A Step-by-Step Guide to Setup LLM locally using Ollama, Python, and ChromaDB | HackerNoon
Briefly

Hosting your own Retrieval-Augmented Generation (RAG) application locally provides full customization, enhanced privacy, data security, control over data processing, and independence from internet connectivity.
Training your model with private data locally ensures data privacy and security, avoiding risks associated with sending sensitive information over the internet.
Local deployment of LLM models mitigates risks of data breaches and misuse, ensuring that your training data, like PDF documents, stays within your secure environment.
Running your chatbot locally guarantees uninterrupted service and access, even in offline scenarios, providing independence from internet connectivity.
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