Build Your Own POWERFUL RAG Chatbot | Python, LangChain, Streamlit

Thomas Janssen · Beginner ·🔍 RAG & Vector Search ·1y ago

Skills: RAG Basics90%Vector Stores60%

Key Takeaways

Builds a RAG chatbot using Python, LangChain, Streamlit, and Pinecone

Original Description

Want to build a RAG-based Chatbot with Python, LangChain, Streamlit and Pinecone? In this video you learn how Retrieval Augmented Generation actually works, how to ingest documents into a database and how to build a chatbot with RAG! 👇Timestamps 👇 00:00 - What is Retrieval Augmented Generation? 01:48 - Environment Setup 03:02 - What does the RAG Ingestion process look like? 06:17 - The RAG Retrieval Process 09:28 - Building a RAG Chatbot with Streamlit 👇Download the code from Github 👇 🔗 https://github.com/ThomasJanssen-tech/LangChain-Pinecone-RAG 👇Follow me 👇 💼 LinkedIn: https://www.linkedin.com/in/thomas--janssen/ ✅ Instagram: https://www.instagram.com/tomstechacademy/ ❗ Some of my videos contain affiliate links. When you click on these kind of links, I get a small percentage in case you make a purchase via the website. Be aware that this doesn't cost you anything - you never pay more than the standard retail price. #python #retrievalaugmentedgeneration #chatbot #streamlit #pinecone #langchain

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Chapters (5)

What is Retrieval Augmented Generation?

1:48 Environment Setup

3:02 What does the RAG Ingestion process look like?

6:17 The RAG Retrieval Process

9:28 Building a RAG Chatbot with Streamlit

Build a Chatbot with RAG in 10 minutes | Python, LangChain, OpenAI