Muskaan NA@Muskaaan03

Bibliotopia is a service that enables you to search books from your descriptions.

This project aims to provide users with a realistic interview experience, thereby boosting their confidence. By simulating real-life interview scenarios, users will get the opportunity to practice and perfect their interview skills, including answering questions, body language, and overall demeanor. Additionally, the project will also help users overcome their anxiety and nervousness, allowing them to perform at their best during actual interviews. This project will be beneficial for job seekers, students, and anyone looking to improve their interview skills. With a focus on helping users achieve their goals, this project will provide an engaging and supportive environment that will encourage users to achieve their full potential. By the end of the project, users will leave with a renewed sense of confidence and the skills they need to succeed in any interview setting.

Chatty Shoes is designed with a highly responsive, scalable and robust backend, leveraging state-of-the-art technology to facilitate user-friendly online shoe shopping via natural language interactions. The backbone of the system is a serverless architecture based on Cloud Functions. This decentralised structure comprises three primary functions: Session Creation, Message Management and Information Retrieval. Session Creation: This function is responsible for initiating conversations with customers. Every conversation represents a unique session, providing the framework for interactive and dynamic dialogues. The data from these sessions, including the conversation history, is securely stored in Firestore, ensuring a persistent and seamless user experience across different sessions. Message Management: Powering the heart of the conversation is a GPT-3.5-turbo, a language model renowned for its ability to understand and generate human-like text. This feature enables Chatty Shoes to handle Frequently Asked Questions (FAQs) within the context of the conversation, thereby giving users instant responses to their queries. Additionally, it provides the AI agent with the ability to perform information retrieval operations on products when the system deems it necessary, making it proactive and more engaging. Information Retrieval: The last key component of the backend is the Semantic Search function, which operates over Pinecone's vectorial database. This feature enhances Chatty Shoes' product recommendation abilities by retrieving product data based on the contextual understanding of user inputs rather than merely keyword matching. This means the AI can effectively understand and respond to nuanced customer preferences, thus improving their overall shopping experience. Together, these elements synergise to create a powerful backend that underpins Chatty Shoes' mission: to revolutionize online shoe shopping by facilitating better, deeper and more intuitive conversations.