NO CODE LLM App to chat with PDFs



Build LLM application to chat with your own PDFs using No Code Tools Flowise and Bubble

What you will 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

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.

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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

Introduction

Introduction

Frontend and Backend

Frontend and Backend of Chat PDF App

Chat Flows for Question Answering PDF using Large Language Models

RAG Flow ( PDF Storage and Answer Retrieval using LLMs like Open AI)

Creating Open AI and Pinecone Secret Keys

How to create Open AI API Key and Pinecone vector database Secret Key

Creating Flowise Fork on Github

How to create Flowise repository fork on Github

Hosting Flowise AI on Render

How to deploy Flowise AI on Render

Creating ChatFlow in Flowise AI – PDF Document Upload

How to create chatflow in Flowise AI – PDF Upload
Test – Chat with PDF uploaded to Pinecone Vector Database

Creating ChatFlow in Flowise AI – PDF Document Query

How to create ChatFlow in Flowise AI – PDF Question Answering
Test – Chat with PDF Uploaded using PDF Query ChatFlow

Bubble – Integrating Flowise ChatFlow APIs

How to integrate Flowise ChatFlow APIs with Bubble

Bubble – Creating PDF Upload Page

How to create PDF Upload Page

Bubble – Creating Chat with PDF Page

How to create conversational style Question Answering Page to chat with PDF

Exploring Flowise AI components

Flowise AI Integrations

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