A Code Implementation to Use Ollama through Google Colab and Building a Local RAG Pipeline on Using DeepSeek-R1 1.5B through Ollama, LangChain, FAISS, and ChromaDB for Q&A

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This tutorial demonstrates building a Retrieval-Augmented Generation (RAG) pipeline using Google Colab and several open-source tools. The pipeline integrates the DeepSeek-R1 1.5B language model using Ollama, LangChain for orchestration, and ChromaDB for vector storage. The process involves setting up the environment, uploading a PDF, and creating embeddings for document retrieval, which are then used to generate context-based answers. This setup provides a scalable, private, and cost-effective solution for real-time information retrieval from documents.