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Development of web application for a gym

Bachelor's thesis is devoted to the development of a unique web application for a gym, which will be competitive in the Latvian market. Within the framework of the project, a web application is being developed, including a server part based on Python language, as well as a client part using such languages as HTML, CSS and JavaScript. The key features of the developed application are integration with artificial intelligence ChatGPT and integration with the third-party application Telegram. Artificial intelligence in this work is presented in the form of chatbot technical support and chatbot online trainer, as well as used to create individual training programmes for each client.The main goal of the work is to create a unique product that has no analogues in the Latvian market, which will significantly improve the experience of gym customers and contribute to the achievement of each client's goals. During the development process testing was performed, which confirmed the successful integration of all components of the application. Based on the testing results, recommendations for further development of the web application are offered.

Author: Andrejs Glušenoks

Supervisor: Olga Dribeņeca

Degree: Bachelor

Year: 2024

Work Language: Latvian

Study programme: Computer Science

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Development of Project Management Assistance Software Enhanced with Generative AI Technologies.

This thesis explores the practical value of applying Generative Artificial Intelligence in project management software to enhance a manager's work. The aim is to evaluate the efficiency and impact of GenAI on project management processes. The research begins with a review of existing academic and industry literature on integrating AI in project management. This is followed by detailed case study analyses of instances where AI has been integrated into project management tools. The Software Development Life Cycle methodology is used to develop and test the software, incorporating a prototyping phase to explore and validate concepts before full-scale development.The results of this study include creating a GenAI-powered software that significantly speeds up the staff selection process for projects by matching project requirements with personnel skills. The findings indicate that the developed software effectively leverages GenAI technologies to enhance the project management process, simplify managerial tasks and contribute to more efficient and accurate decision-making processes. This research highlights the potential of GenAI to transform project management practices and drive future innovations.

Author: Pāvels Kulajevs

Supervisor: Aleksejs Vesjolijs

Degree: Bachelor

Year: 2024

Work Language: Latvian

Study programme: Computer Science

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Web service development for the enterprise

The aim of the work is to develop a website for a car service in accordance with the functional and non-functional requirements of a company that previously did not have a personal website. This website should help the company attract new customers, as well as retain existing ones, thanks to a more detailed description of all services provided and a pleasant interface. One of the main goals of this work is: to examine and compare an internet site that was developed using the classical method and a website whose code was written using artificial intelligence, and to provide an assessment of certain results.To find out which features are useful and what customers really want to see on the site, a survey of potential customers was conducted.Analyzing the subject areas, web pages with similar functionality were analyzed and identified, as well as the initial requirements for the website.At the design stage, development tools were analyzed and selected, a preliminary page design was developed, use case diagrams, page navigation tree were created.Also, when the code was written, manual testing was done, as well as code testing in individual applications.After the work was completed and the code was written, certain tests and code reviews were performed. The code was then fixed.

Author: Radions Kasmausks

Supervisor: Boriss Mišņevs

Degree: Bachelor

Year: 2024

Work Language: Latvian

Study programme: Computer Science

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Enhancement Strategies for Retrieval-Augmented Generation Systems

This thesis systematically explores the enhancement of Retrieval-Augmented Generation (RAG) systems within Large Language Models, emphasizing optimization of retrieval parameters and generation accuracy. We investigate optimal configurations in RAG systems, including chunk size and overlap percentages, top-k selection, query transformations, different retrieval methods, different LLMs, namely GPT-3.5-Turbo and GPT-4, discovering that a chunk size of 500 tokens generally offers the best performance. Vector search using cosine similarity emerges as the most effective retrieval method, significantly enhancing both context precision and recall across various tasks and knowledge bases. Experimentation within the CRUD-RAG framework demonstrates its applicability in diverse tasks from content creation to knowledge refinement. Our findings indicate that enhancements in retrieval settings can markedly improve the performance of RAG systems, making them more efficient and adaptable for complex information synthesis and retrieval tasks. These results affirm the potential of systematic enhancements to improve AI-driven language models in practical applications, contributing significant insights and practical approaches to the evolving landscape of RAG system research.

Author: Sigita Lapiņa

Supervisor: Dmitry Pavlyuk

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

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Research on Software Development Aspects Using node.js Technology

To explore the aspects of software development, an application was created using Node.js and NestJS to build a REST API. This API integrates Google Natural Language AI to analyze submitted user reviews. The application includes multiple REST API endpoints that can process, analyze, and aggregate user review data. Performance measurements were conducted, analyzing event loop latency, memory and CPU usage, and other key metrics. MongoDB was used for data storage. The work also includes API and its performance evaluation. The system was tested to ensure it meets the set criteria and provides practical application.

Author: Valērijs Sergejevs

Supervisor: Mihails Savrasovs

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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