Building no-code low-code RAG Application Using LangFlow
In this video, I will explore Langflow, a no-code low-code tool for building AI applications using drag-and-drop functionality. The video is divided into two parts: the first shows creating simple chat applications and second creating retrieval-augmented generation (RAG) applications using Lang Flow's managed service.
Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.
✨ Core features
Python-based and agnostic to models, APIs, data sources, or databases.
Visual IDE for drag-and-drop building and testing of workflows.
Playground to immediately test and iterate workflows with step-by-step control.
Multi-agent orchestration and conversation management and retrieval.
Free cloud service to get started in minutes with no setup.
Publish as an API or export as a Python application.
Observability with LangSmith, LangFuse, or LangWatch integration.
Enterprise-grade security and scalability with free DataStax Langflow cloud service.
Customize workflows or create flows entirely just using Python.
Ecosystem integrations as reusable components for any model, API or database.
Link ⛓️💥
https://www.langflow.org/
https://platform.openai.com/settings/...
Timestamps ⏰
00:00 Introduction
00:56 Video Structure and Overview
01:38 Exploring the Lang Flow Website
02:24 Navigating the Lang Flow Documentation
04:13 Setting Up and Signing In
05:20 Understanding the Lang Flow UI
06:03 Creating a Basic Prompting Flow
14:55 Implementing the Rag Flow
26:15 Conclusion and Next Steps
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