How to use ChatGPT API to build a chatbot for product recommendations with embeddings

Are you looking to build a chatbot that can recommend products to your customers based on their unique profile?
Here's a step-by-step guide that shows you how to build a chatbot using embeddings to match a user's profile with relevant products from a company's database.

Need tailored AI solutions?
I provide one-on-one collaboration and custom AI services for businesses.

Let's find the perfect solution for your challenges: consulting services

---

Outline

1. Introduction to embeddings

2. Get OpenAI API keys

3. Create a product dataset

4. Create embeddings for product dataset

5. Create a customer profile dataset

6. Create embeddings for customer profile dataset

7. Create embeddings for customer chat message

8. Get previous purchase data similarities

9. Get product database similarities

10. Create ChatGPT API prompt

11. Create ChatGPT product recommendations

---

Here's what we'll use:

1. OpenAI API 🤖

2. Python 🐍

---

Detailed walkthrough

Read blog post for a detailed walkthrough: https://norahsakal.com/blog/chatgpt-product-recommendation-embeddings

Troubleshooting

attributeError: module 'openai' has no attribute 'ChatCompletion'

This probably means that the version of your Python client library for the OpenAI API is lower than 0.27.0.

Run pip install openai --upgrade in your terminal for the latest version and make sure it is at least 0.27.0:

---

InvalidRequestError: This model's maximum context length is 4096 tokens

This indicates that the input message_object sent to the ChatGPT API has exceeded the maximum allowed length of 4096 tokens.

You will need to shorten the length of your messages to resolve the issue:

---

Do you need help with getting started with the ChatGPT API? Or do you have other questions?
I'm happy to help, don't hesitate to reach out ➡️ [email protected]