Time is the ultimate currency.
Stop wasting your life away looking for that document containing that one statistic you vaguely remember from 8 months ago.
“Is our y1-y2 retention rate 34% or 45%?”
Just ask the AI, silly.
I want to show you how to build an AI chatbot, powered by ChatGPT, that uses your own data.
A few weeks ago, I wrote about AI chatbots built on your own data in this post.
I decided to follow the Google Colab instructions from Dan Shipper who created chatbots for Lenny’s Newsletter and Andrew Huberman.
It was a little out of date so I made some updates to the code.
I figure many of the companies offering to create chatbots are powered by OpenAI.
It’s also important to understand how the underlying technology works!
So here are the basic steps to create your own chatbot with OpenAI:
Download the text you want to embed the AI with
Install OpenAI and LangChain dependencies
Define functions you will use later
construct_index()
ask_chatbot()
Set OpenAI API Key
Construct_index() - costs $
This is where you pay OpenAI to embed your text or “index”
Ask away with ask_chatbot() - costs $
Chatbot in action
Next steps to improve the chatbot:
create a pretty webpage for it
use pinecone, a vector database, to store the embeddings
Takeaways for Marketing
You can do this with your own knowledge base and chat with it.
Here are some sample questions:
What’s the best creative concept last quarter?
What’s our best performing headline?
What’s a good trial to subscribe rate?
What’s a good install to trial rate?
What’s the average CPI in the US?
Who’s our highest LTV demographic?
What are our best performing days of the week/hours of the day?
How many hours a month will a customized AI chatbot save your org?
Stop wasting time. Combine the power of ChatGPT and your own data.
Ping me at manson@goparabolica.com for help.
This is valuable cutting edge AI info. I heard about embeddings but your article helped me clarify it better and see how it can be used with a library to bring it to your own AI app