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Developing LLM powered chatbot for customer support

Instructor led workshop for creating a customer support chat bot using LLM and Agentic RAG.

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4.7

Rating

10 Hrs

Duration

Advance

Level

10

Assignments

What you'll learn

How to create a chat bot Q&A chat bot using python and LLM
How to add RAG feature for advance level answering
How to connect the bot with database for real time updates

Who should take this course

Ideal for anyone with python programming and LLM knowledge
It is recommended to do the “LLM for beginners” training before joining this course
It is recommended to do the “AI Agents for beginners” training before joining this course

Skills you'll gain

LLM
Chat Bot
Agentic RAG
Streamlit
Python
SQL Agents
AI Agents

Course contents

Set up the LLM API
From the domain get the F&Q and store it in a text file
Create the RAG pipeline
Evaluate bot’s performance metrics

Creating demo web UI in python streamlit

Instead of F&Q pass a document to RAG pipeline
Ability to handle out of context questions
Evaluate bot’s performance metrics

Instead of single document, bot can search multiple documents for answering
Evaluate bot’s performance metrics

We will use a prebuilt SQL Agent to convert natural language to SQL query
Ability to fetch required details from Database for answering
Evaluate bot’s performance metrics

AI Agents for beginners

This course will focus on understanding AI agents and how to use them create persona to perform complex, multi-step actions and make decisions independently.

LLM RAG for beginners

This course includes how to uses LLM and prompt engineering for question answering, reasoning, text summarization ect. Also allowing LLM to access knowledge from external sources using RAG.

Extracting structured output from documents using LLM

In this workshop a PDF based Q&A solution will be devloped from scratch, where user can ask question to PDF and get answers.