Year: 2024
Type: dissertation
Abstract: Fast advancements in generative AI and capabilities of large language models disrupt software development industry. Case company faced a challenge with providing relevant consultancy offering for LLM models integration and development of LLM powered applications. This study provides applied knowledge about LLMs, their strengths and limitations and explores architecture of LLM powered applications. \n \nLLMs show exciting capabilities in processing and generating natural language, but they lack specific domain or up-to-date knowledge, reasoning capabilities, and abilities to interact with external services and APIs. Enhancing LLMs with memory and helper tools provides numerous opportunities for development of capable conversational applications and assistants, that can be considered as a new type of software. \n \nDemo LLM powered application is developed as outcome of this thesis. Development starts with basic structure of LLM powered application, which is progressively enhanced with memory, external data store and ability to invoke custom actions. Application interface, monitoring and deployment are discussed as well and form a complete solution to the research problem. Finally, challenges faced during implementation and obtained results are discussed alongside with improvement suggestions.
Source: Theseus (Ammattikorkeakoulujen)
Author: Elizarov, Oleg
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7045259363