CloseChat.ai
Client:
ItalyIndustry: E-commerce Store Owners, Small to Medium E-commerce Enterprises SMEs
Audience:
E-commerce Solutions/Customer Interaction PlatformsTech Stack:
React, Next, MUI, Node.js, TypescriptStatus:
Ongoing
In this project we develop a website and a shopify app. In the website you need to do registration and after that you install a closechat.ai app in shopify store that help help to measure the all orders from your store and track your store performance based on your order. It will also create a chatbot on your shopify website and through which customer can ask any information of store like give best product from your store etc. chatbot can also give order information of customer.
Make shopify app that gives us shopify store information and store that information
Fetch the order data from shopify store and also get live order data from it
Fetch the shop information from shopify
Create a common chatbot that will answer the user questions and answer should based on different different store
Import the external data in chatbot with 5 types. Like single page website, multiple page website, pdf, text, csv file
We have feature of chatbot which can be implemented using socketIO from node backend but because of it&aposs live connection so it can increase the load on backend server implemented using node
Create shopify app in nodejs and that will generate access token with help of it we can access the store information
Call the shopify order api that require a access token and get the data also create a webhook that help to fetch the live data
Call the shop api of shopify that helps to get the shop information
We need to create a embedding from the data we pass so that it will give us faster response and also it will take a small space in storage and make a chatbot using langchains model that will read data from embeddings
Create a index in data and on that index we append the data that we get in api, use different langchain reader like pdf csv and text based on that we fetch data from that file format
Throughout the project execution, our focus has been on seamless integration and optimal functionality. We initiated by creating a Shopify app in Node.js, facilitating access token generation for store information retrieval. Utilizing Shopify APIs and webhooks, we successfully obtained both static and live order data. To enhance chatbot efficiency, we employed language embedding for faster responses, integrating multiple data formats using various language models. Leveraging Amazon API Gateway and serverless Lambda functions, we implemented sockets for improved application performance. This comprehensive approach ensures efficient Shopify app functionality, robust data handling, and enhanced user interaction within the platform.
