Скачать с ютуб 100% Local RAG Using LangChain, DeepSeek, Ollama, Qdrant, Docling, Huggingface & Chainlit в хорошем качестве

100% Local RAG Using LangChain, DeepSeek, Ollama, Qdrant, Docling, Huggingface & Chainlit

In this video, we create a fully local Retrieval-Augmented Generation (RAG) application using the DeepSeek model via Ollama. The architecture involves utilising Docling to extract information from PDFs, segmenting the document into smaller chunks, and then embedding these segments using HuggingFace embeddings. The segments are stored in a local Qdrant Vectorstore using Docker. When a query is made, embeddings are generated and queried against the knowledge base to retrieve relevant information. We leverage LangChain for orchestration and interface with a UI bot using Chainlit, implementing a step-by-step approach that highlights the capabilities of DeepSeek in handling and reasoning over the retrieved data. The video also discusses prerequisites like installing Docker and setting up the environment, while walking through the code implementation and testing the application with sample queries. TimeStamps ⏰ 00:00 Introduction 00:10 Understanding the Architecture 01:50 Setting Up the Environment 04:03 Ingesting Documents 04:58 Creating the Vector Database 07:30 Running the Application 14:59 Using the UI and Asking Questions 22:10 Conclusion and Final Thoughts Links ⛓️‍💥 https://ollama.com/ https://qdrant.tech/documentation/qui... https://www.docker.com/get-started/ https://docs.phidata.com/introduction https://blog.gopenai.com/how-to-build... https://ds4sd.github.io/docling/examp... https://github.com/sudarshan-koirala/... ------------------------------------------------------------------------------------------ ☕ Buy me a Coffee: https://ko-fi.com/datasciencebasics ✌️Patreon:   / datasciencebasics   ------------------------------------------------------------------------------------------ 🤝 Connect with me: 📺 Youtube:    / @datasciencebasics   👔 LinkedIn:   / sudarshan-koirala   🐦 Twitter:   / mesudarshan   🔉Medium:   / sudarshan-koirala   💼 Consulting: https://topmate.io/sudarshan_koirala #ollama #deepseek #qdrant #langchain #chainlit #docling