#24 Build Agentic RAG System from Scratch | Agentic RAG Pipeline | Advanced RAG with AI Agents #ai

Description

In this video, we will discuss Agentic RAG - a more advanced approach than normal RAG systems! Learn the key differences between Normal RAG and Agentic RAG, and build a complete Agentic RAG system from scratch. 🎯 Key Components: - Retriever tool with docstring for agent understanding - LLM (GPT-4o) for agent intelligence - System prompt for agent behavior - Tool decorator for function-to-tool conversion - Agent repeatedly calls tools until accurate results 💻 Technologies Used: Python | LangChain | OpenAI | PyPDF | Vector Embeddings | AI Agents | InMemoryVectorStore IMPORTANT RESOURCES: 📂 GitHub Repository: https://github.com/techsimpluslearning/Complete-GenAI-Course-Python-Langchain If you have any questions or doubts, feel free to reach out to me. 📞 Schedule 1-to-1 Call: https://topmate.io/techsimplus_learnings Enjoying the content? LIKE 👍 this Video, SUBSCRIBE 🔔 for Data Science, Machine Learning, Deep Learning and Generative AI tutorials, and COMMENT below if you have any questions, doubts or Suggestions! 🚀 Let's master GenAI together! 🚀🔥 #generativeai #langchain #python #ai #machinelearning #aiprojects #langgraph #rag #aiagents #openai #gemini #awsbedrock #fastapi #modelcontextprotocol #streamlit #aitutorial #learnai #coding #programming #indianyoutuber #hinditutorial #techeducation #aicourses #portfolio #careergrowth #vectordatabases #aideployment #2026 #deeplearning #nlp #chatgpt #gemini #genai #techsimplus