Welcome to Generative Geek! In this video, I'll walk you through how to build a powerful PDF-based Question and Answer (Q&A) RAG (Retrieval Augmented Generation) system using Langflow, OpenAI, and Chroma DB, all without writing any advanced code. Langflow offers a no-code/low-code solution that simplifies the process of creating complex LangChain-based LLM applications with an intuitive drag-and-drop interface.

What You'll Learn:
- Introduction to Langflow: Discover the capabilities of this no-code platform.
- Setting Up Your Environment: Quick guide to get you started with Langflow, OpenAI, and Chroma DB.
- Building the PDF Q&A RAG System: Step-by-step tutorial on how to use Langflow to create a robust Q&A RAG system.
- Integrating OpenAI: Learn how to harness the power of OpenAI for intelligent Q&A.
- Using Chroma DB: Understand how to leverage Chroma DB for efficient data management.

Chapters:
(00:00) Introduction
(02:20) Installing Langflow
(05:15) Error fix
(06:50) Quick UI walkthrough of Langflow
(08:46) File reader Component
(09:07) Text Splitter Component
(09:45) Connecting two components
(10:15) Chroma Vector Store component
(11:15) OpenAI Embeddings Component
(11:40) Creating a Global Variable in Langflow
(13:50) Adding various input components
(15:00) Building the Prompt Template
(17:00) Adding memory to Chatbot
(19:30) Adding Chroma Vector Search
(22:50) Adding OpenAI Component
(24:50) Playground and Debug


Why Watch This Video?
- No Code/Low Code: Perfect for beginners and non-programmers.
- Comprehensive Tutorial: Detailed instructions to guide you through each step.
- Quick Learning: Build your RAG application in less than 20 minutes!

Useful Links:
- Langflow Github - https://github.com/langflow-ai/langflow
- OpenAI API Key - https://platform.openai.com


Follow Me:
- LinkedIn:   / vaibhavpandey  

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