GitHub-based Flowise AI Installation & Practical Example with LangChang Documentation Reference

Flowise AI is an open-source UI visual tool for building Language Learning Model (LLM) apps. Flowise AI is based on LangChain, a framework for developing context-aware applications with natural language processing (NLP) and artificial intelligence (AI).
In this video, I showcase how to install Flowise AI, and use its drag-and-drop interface to create our own custom LLM flow while explaining the theoretical concepts of LangChain that power this flow.
Whether you are a beginner or an expert in LLM, Flowise AI and LangChain can help you create amazing applications that leverage the power of language models. I hope you enjoy the video and find it useful. Please let me know what you think in the comments and feel free to share it with your network.
Flowise Official website: flowiseai.com/
You can also check out the Flowise AI GitHub repository here: github.com/FlowiseAI/Flowise
And the LangChain website here: www.langchain.com/
Thank you and happy coding! 😊
0:00 Introduction
0:25 Low Code, No Code Platform
1:00 LangChain Framework & RAG architecture
2:42 Installation
4:22 Practical Example Use Case
5:35 Documents
6:40 Text Splitters
8:36 Embeddings
8:55 Vector Store
10:20 OpenAI API Key
11:03 Conversational Retrieval QA Chain
12:50 Chat with Bot
13:26 Tokens
14:07 Tokenizer
14:22 LLM Pricing

[@varunmehra5]

Can you also do a tutorial on using custom tool to make a request to external API or a webhook and get the response back to push into the flow?