Our project offers a user-friendly webUI that brings together latest technologies for easy task execution. Users can effortlessly interact with Docker containers, manage AWS services, set up a Hadoop cluster for storing data across multiple systems, and automate jobs using Jenkins. The backend powered by Python CGI ensures robust functionality.
We've created a smart chatbot using generative AI that engages users in interactive conversations. With computer vision, users can experience real-time face detection, background blur, distance measurement, and volume adjustments for an exciting user interface. Machine learning enables us to train models for various tasks, making this project a powerful and versatile solution for multiple uses.
Linux: We have used linux for server hosting, cloud infrastructure, and development environments. Known for stability, security, and flexibility in managing resources.
Containerization: Our project utilizes Docker for container and service management, enabling seamless scaling and deployment, simplifying the process for developers.
AWS Cloud: we seamlessly integrated and implemented a range of AWS cloud services, including EC2, S3, API Gateway, SNS, SES, EBS, and Lambda. These services collectively provide a robust and scalable cloud infrastructure, enabling efficient data storage, communication, computation, and event-driven functionalities for the entire platform.
Python: we employed Python as the backend CGI to automate tasks such as sending SMS and emails. Users can easily input the required details, and Python handles the automation process, making it hassle-free and efficient.
Hadoop: we used Hadoop to store data across multiple systems, allowing us to process big data and analytics tasks in parallel. This approach ensures faster and more efficient data handling, making it easier to work with large amounts of data. Jenkins: Jenkins is utilized as an automation tool in this project to streamline and automate various tasks, simplifying the deployment and management of the integrated technologies. Generative AI: we harnessed the power of LLM (Large Language Model) and the Langchain framework to create an advanced chatbot. This chatbot is equipped with the ability to provide real-time answers to user queries. By fetching relevant data from LinkedIn, the chatbot offers up-to-date and accurate responses, enhancing its effectiveness and usefulness for users. And we created a custom chatbot using ChatGPT, enabling smarter and personalized conversations with users. This AI-powered tool enhanced user interactions and made the chatbot responsive to their needs.
Web Development Tools: we developed the front end using HTML, CSS, and JavaScript, creating an intuitive and visually appealing user interface. The combination of these web technologies ensures a seamless and interactive experience for users while accessing the various features and functionalities of the integrated platform.
Machine Learning: we used different machine learning algorithms like Regression, Multi-Linear Regression, OpenCV, and CNN (Convolutional Neural Network). These algorithms make the system smart and capable of tasks like data prediction, image processing, and recognizing patterns, making the overall experience for users much better.
Computer Vision: Computer vision models are used to implement real-time face detection and recognition capabilities in video interactions. This ensures that the platform can identify faces accurately, which is essential for features like background blurring and face distance measurement, volume adjustment and many more.
This project brings together advanced technologies to create a user-friendly platform. The web interface makes complex tasks easy by using AWS, Hadoop, Docker, and Jenkins for efficient cloud operations. The machine learning features enable real-time face detection and volume adjustment. The custom chatbot enhances user interactions, making it a versatile and powerful solution for various purposes. Overall, this project provides convenience and a seamless experience for users.
In the future, we'll use Jenkins more to automate tasks like software updates. We'll also use Kubernetes to manage containers, making it easier to handle different parts of our project. With Ansible and Terraform, we can automatically set up and manage our cloud infrastructure without any manual work. Additionally, we'll make the website easier to use and navigate, so anyone can perform tasks effortlessly. These improvements will make our project even better, providing efficiency and convenience for all users.