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NO CODE LLM App to chat with PDFs
Rating: 4.7 out of 5(61 ratings)
2,488 students

NO CODE LLM App to chat with PDFs

Build LLM application to chat with your own PDFs using No Code Tools Flowise and Bubble
Last updated 9/2023
English

What you'll learn

  • Build NO CODE LLM application to chat with your PDFs
  • Create chatflows on Open Source NO CODE Langchain Based Platform- FLOWISE
  • Create UI on NO CODE platform BUBBLE , and integrate with Flowise APIs
  • Create API Keys on OpenAI and Pinecone vector database

Course content

12 sections14 lectures37m total length
  • Introduction0:48

    Have a look into snapshot of the demo Chat PDF app ,  that will be built during this course .

    No Code Tools Used - Flowise and Bubble

Requirements

  • No programming experience needed . You will learn everything you need to know !

Description

Elaborate step by step tutorial to create an application to chat with your own PDFs , using No Code Tools Flowise AI and Bubble .

With no prior programming experience needed, you will learn how Question Answering with Private Data works , and will be able to create demo application , using power of Generative AI and Large Language Models like Open AI


No Code Tools Used :

  1. Flowise AI 

  2. Bubble[dot]io

What is Flowise AI :

Flowise AI is a drag-and-drop interface for creating LLM flows using LangchainJS. It is an open-source project on GitHub that allows you to construct LLM apps fast and effortlessly. Flowise is a strong tool for experimenting with LLMs and developing LLM-based apps.


What is Bubble[dot]io :

Bubble[dot]io is a no-code app development framework that lets you design, develop, host, and scale applications without writing any code.

In simple words, Bubble is an online platform that allows users to develop applications without writing code. You build the application using a drag-and-drop interface in the browser, and then Bubble acts as the platform that serves your application.

Primarily appealing to non-technical users who want to build no-code web applications without knowing the industry's traditional tools.


Topics Covered:

  • Retrieval Augmented Generation (RAG) flow for Question Answering using Generative AI

  • Creating Open AI API Key and Pinecone vector database secret key

  • Creating Fork for Flowise AI on GitHub

  • Deploying Flowise AI on Render

  • Creating Chatflow for PDF upload on Flowise AI

  • Creating Chatflow for PDF Query on Flowise AI 

  • Creating Landing Page Chatbot via Embedding

  • Creating PDF Upload Page on Bubble and integrating with Flowise AI API 

  • Creating PDF Question Answering Page on Bubble and integrating with Flowise AI API 

  • Exploring Flowise AI Features



Who this course is for:

  • People with no programming experience curious about Large Language Model based applications