Build One ChatBot for MultiDatabase: CSV, PDFs and Images | Step-by-Step Tutorial

Discover how to build a versatile chatbot that interacts with multiple databases from scratch! 🚀
In this tutorial, you'll learn:

How to classify user queries with LLMs to determine if they require database interaction.
Integrating CSV files, PDFs in VectorDB, and images in VectorDB into your chatbot.
Automating script execution for the relevant database.
Whether it's a simple question or a database lookup, this chatbot dynamically handles it all!
🔗 Key Topics Covered:
✅ LLM-driven query classification
✅ Setting up and using VectorDB for PDFs and images
✅ Step-by-step guide to combining databases in one chatbot

🎯 Perfect for developers looking to enhance chatbot capabilities with AI and database integration.

📖 Chapters:
00:00 Introduction
00:21 Project Demo
03:05 Code Explanation
05:32 Image DataSet Integration
10:02 PDF Data Integration
14:08 Final App Integration

🔗 GitHub Code Repository:

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#ChatBotDevelopment #AI #aiapplications #chatbot #rag #generativeai #llm

[feelingmatters.]

Hello, I tried but when ever I asked question related to image or finetuning doc, the decisions were made correct through llm but its not giving the final response in the streamlit app, and in vs code terminal its getting terminated without any error but for 'normal' and 'Grocery' its working fine in app. Could me help me on that?

[ecmscapgemini]

brother, can u please tell how to setup api key in .env file? There is no such .env in the Github repo and am completely unaware of how to put api key in the file (even though I have the api key).

[SathishR-lo]

Errors while executing where to contact

[rakeshkumarrout]

Hey this is quite informative, could you make a video on livekit integration with any rag application.with our own frontend?