Learn how to build a RAG (Retrieval-Augmented Generation) system locally for financial document analysis using DeepSeek-R1 and Ollama! Perfect for coders, finance pros, or AI enthusiasts, this tutorial by kgp talkie covers:
πΉ Uploading & processing PDFs into a vector database (FAISS)
πΉ Running DeepSeek-R1 7B model locally via Ollama
πΉ Setting up private AI workflows for sensitive financial data
πΉ Asking questions like "Whatβs the quarterly revenue?" and getting instant answers
Tools Used:
β
DeepSeek-R1 (1.5B/7B models for coding & finance)
β
Ollama (local AI model runner)
β
Streamlit (web interface)
β
LangChain (RAG pipelines)
π Like if you love local AI solutions!
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#kgptalkie #DeepSeekR1 #OllamaTutorial #FinanceRAG #LocalAI #DeepSeekR1onOllama #RunDeepSeekLocally #FinancialAnalysis #RAGtutorial #PrivateAI #OllamaSetup #DeepSeekR1Tutorial #FAISS #LangChain #NoCloudAI #DocumentQA #DeepSeek7B #AIForCoding #SensitiveDataAI #OfflineRAG
Links
Dataset
https://github.com/laxmimerit/rag-dataset
Code Files
https://github.com/laxmimerit/ollama-chatbot
Local LLM Playlist
https://www.youtube.com/watch?v=sNSoQ7k0JFY&list=PLc2rvfiptPSReropGbvDFpB6dneNBwqhD
Ollama Setup for DeepSeek R1
https://www.youtube.com/watch?v=wuBTqk6DbV0&list=PLc2rvfiptPSReropGbvDFpB6dneNBwqhD&index=7
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