Skip to content

quamernasim/AI-Chatbot-Using-Mixtral-8x7B-PGVector-Llama-Index-With-Websockets-For-SaaS

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

25 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Steps to Building an AI Chatbot Using Mixtral 8x7B for SaaS Entrepreneurs

An AI based chatbot built for SaaS Entrepreneurs

Introduction

This is a step-by-step guide to building an AI chatbot using Mixtral 8x7B for SaaS Entrepreneurs. The guide is designed to help you understand the process of building an AI chatbot and how it can be used to improve your business.

What is Mixtral 8x7B?

Mixtral 8x7B is LLM released by Mistral AI. It is a powerful LLM that has performed well on a variety of language tasks. It is a Mixure of Experts Model. It has outperformed GPT-3 on a variety of language tasks. It is a powerful tool for building AI chatbots.

Why Build an AI Chatbot?

AI chatbots are becoming increasingly popular in the business world. They can be used to automate customer service, answer questions, and provide information to customers. They can also be used to improve the user experience on your website or app. Building an AI chatbot can help you save time and money, and improve the overall customer experience.

How to Build an AI Chatbot Using Mixtral 8x7B

Building an AI chatbot using Mixtral 8x7B is a relatively simple process. Here are the steps you need to follow:

  • Step 1: Collect Data
  • Step 2: Index The Data using Llama-Index
  • Step 3: Store The Indexed Data in a Database (In our case, we will use PGVector)
  • Step 4: Get the LLM and Embedding Model from Hugging Face
  • Step 5: Load the indexed data from the database
  • Step 6: Set up a query engine using llama-index
  • Step 7: Combine all the above steps to build an AI chatbot
  • Step 8: Finallly, integrate the chatbot with WebSockets
  • Step 9: Test the chatbot

How to Use the AI Chatbot

Once you have built the AI chatbot, you can use it to automate customer service, answer questions, and provide information to customers. You can also use it to improve the user experience on your website or app. The possibilities are endless!

app.py that contains the websockets code to integrate the chatbot with your website or app.

To run the chatbot, you can use the following command: bash python app.py --device cuda

To test the chatbot, you can use the following command: bash python test_app.py --message "What is this chatbot about?"

Conclusion

Building an AI chatbot using Mixtral 8x7B is a relatively simple process. It can help you save time and money, and improve the overall customer experience.

References