Chatbot( content affinity recommendation)

Tool Requirement Environment. Python 3.6 SQL SERVER DATABASE/ postgreSQL Project goal I am launching an e-mail campaign for the marketing that e-mail will contain short information about the product along with “Read more”. Button. Once the customer clicks the read more button, it will go to my company webpage; where I hosted my content under blogs (example). there one can see the full content of the article based on their interested chatbot will recommend a similar type of articles to them Think about as below the SQL SERVER database contains “customer_table” in that table each customer has their- First name, last name, e-mail_id, date of enrolled, last visit date, URL (previous read) are available. Now I wanted to make a chatbot as below requirement Step1: As soon as customer land in the page, the chat window has to pop up and interact with them starting by greetings words based on their last name/first name from customer_table1 ( you need to set up greetings and other ( sample questions) in the same table (customer_table) and the reply answer need to store in the same table by customer wise Step 2: at the same time the code has to read the whole content during their reading and do the NLP extract meaning full words and store it in the same table (variable name: key_word”) by each customer (note: this place whenever the customer read new article, the NLP process will do and store it new words without duplicates) Step 3. Based on the customer interest from “keyword” column from the table the chatbot has to recommend the new article from the previous Url Step 4: if they are the new customer then it has to ask their details (such as first, last name, email_id etc., followed by thanks words ( encouraging’s words to the customer to keep interactive) Step 5 I need to capture into the database table of their browsing history(such as click date, click time, click-end time) Hope, you could understand my requirements (I want a content-based recommendation through Chatbot NLP) Finally, you need to implement in my mac laptop and show the demo, Let me know ho can achieve ASAP.