Easy RAG AI Upgrade with Re Ranking скачать в хорошем качестве

Easy RAG AI Upgrade with Re Ranking

Want to make your RAG AI smarter and more accurate? In this video, we’ll show you how to easily upgrade your Retrieval-Augmented Generation (RAG) system using **re-ranking**. With this simple technique, you can improve the quality of responses by ensuring the most relevant information is selected first. We assume you already installed made a simple RAG app using ollama, langchain, and chromadb, if not, please refer to video about building your own RAG AI at:    • Build Your Own RAG AI with Ollama, LangCha...   Timestamps: 0:00 Overview 0:44 Use Re-Ranking to improve quality of context 6:32 Install Streamlit 6:57 Use Streamlit to improve user interface 12:13 Troubleshoot ollama 13:09 Explain with example about difference between using and not using re-ranking 17:06 Process documents in different folders and query based on those documents Links used in video: Go here to get rules pdf for Ticket to Ride: https://www.daysofwonder.com/ticket-t... Links to code files: rag_console.py and rag_app.py file with python code for the RAG app is at: https://github.com/gbrlno/rag_app Commands used in video: .venv\Scripts\activate.bat code . ollama ps ollama list ollama run llama3.2 /bye python rag_console.py pip install streamlit streamlit run rag_app.py #AI #MachineLearning #RAGAI #ReRanking #ArtificialIntelligence #LangChain #ChromaDB #Ollama #Streamlit #AIAutomation