Using Flask we are going to add a webhook route to receive message updates. You will have to put your documents in the `documents` folder chatbotģ. Here is the basic structure of our project so far. Phone_number_id="whatsapp phone number id" Use WhatsApp credentials obtained at getting credentials openai_key ="your open ai key" Using your favorite text editor, create a. env file to hold our credentials from WhatsApp and OpenAI. Pip3 install flask additional required packages packageĮnables us to work with WhatsApp cloud API So we have to install all our packages on the local machine.Īt this step, it is assumed that you already have the packages discussed in the previous article installed. With ngrok everything is done on your local machine. I will be going through with ngrok and replit Ngrok There are several ways you can set up a webhook. We shall set up a webhook to receive WhatsApp message updates. It's time to get our hands on work, we are going to make minor modifications to the previous code. With your phone_number_id and whatsapp_token, we are ready to integrate our bot with WhatsApp. To get your WhatsApp cloud API creds, please follow the instructions at whatsapp cloud api set up. The basic setup of the WhatsApp chatbot is obtaining credentials. We are going to modify a bit our previous code to accomplish this amazing feature using heyoo wrapper. Let's go with one of the popular social platforms, WhatsApp. ![]() Now we are going to make a bot more useful by making it available on various platforms. ![]() In the post-chatbot form document using chatGPT, we were able to create a chatbot from our documents. In this article, we are going to create a bot and deploy it in WhatsApp. With the ability to create your own chatbot from documents, you will need to put it out in the world to see it in action.
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