Building a RAG-Powered Chatbot | using Langchain(TS/JS), AI SDK, Pinecone DB, Open AI & Next.js 15

Описание: Learn how to build a powerful PDF chatbot using Retrieval-Augmented Generation (RAG) with Next.js, LangChain, and Pinecone. This tutorial shows you how to create a chatbot that can understand and answer questions about any PDF document you upload.

SOURCE CODE : https://github.com/MUKE-coder/pdf-chat
BLOG : https://codemint-gamma.vercel.app/blo...

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🛠 Technologies Used:
Next.js
LangChain
Pinecone
OpenAI
Tailwind CSS

🔗 Important Links:
Pinecone: https://www.pinecone.io
LangChain: https://js.langchain.com
Next.js: https://nextjs.org

TIME STATMPS
00:00 Introduction.
04:29 Getting started with Rag-powered chatbot
07:43 Show casing first level of ai integration (chatbot)
10:28 Going through the documentation, Research , inspiration , Successes, and Challenges of the application (chatbot).
20:40 Installing a next-js application.
22:34 Understanding large language models(LLMs)
32:38 Understanding Retrieval-Augmented Generation (RAG) using the Code mint documentation.
49:55 How to set-up OpenAi Api Keys.
52:49 Getting started / setting-up Pinecone database (setup process).
55:21 Setting up PDF URL containing the knowledge base.
1:02:21 Project set up including shadcn installation, setting up pinecone db and setting up uploadthing.
1:18:35 Understanding more on the application architecture.
1:21:50 Creating and set up Pinecone Client.
1:27:37 Create Pdf Processing.
1:28:05 How to use lang-chain and usage.
1:48:27 Storing the data in the PineconeDB and setting up the vector-store
1:52:04 Creating a server action to prepare ,Chuck it and store it.
1:54:52 Creating a file upload page
2:00:40 Testing and running the application.
2:17:27 Creating the Chat API Route and configuration of the ai chat-bot.
2:37:32 Testing and debugging the ai chat-bot.
3:23:13 Final solution / conclusion

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