If you’re exploring the world of Retrieval-Augmented Generation (RAG) and want to run it locally, here’s a quick guide to get started with Ollama and DeepSeek!
Why Ollama?
Ollama is a fantastic tool for running LLMs locally, making it easy to experiment with models like DeepSeek without needing cloud infrastructure. It’s lightweight, fast, and perfect for developers who want to keep things simple.
How to Build a Local RAG System:
- Install Ollama: Download and set up Ollama on your local machine.
- Load DeepSeek: Use Ollama to load the DeepSeek model locally.
- Set Up Retrieval: Integrate a local vector database (e.g., FAISS or Weaviate) to handle document retrieval.
- Combine RAG: Use a framework like LangChain to tie DeepSeek and your retrieval system together.
Why Go Local?
Running RAG locally gives you full control over your data, ensures privacy, and allows for customization without relying on external APIs.