Design and Implementation of a Multi-Modal, Agentic Code Companion System (ICC) using Fine-Tuned Code LLMs and Structured Visualization

• Author(s): Kunal Kumar Nath; Samridh Chauhan; Tanmay Jadhav; Pranit Virkar
• Paper ID: 1711930
• Page: 659-669
• Published Date: 12-11-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 5 November-2025
• DOI: https://doi.org/10.64388/IREV9I5-1711930

Abstract

This paper proposes the architectural design and implementation strategy for the Intelligent Code Companion (ICC) system, a novel platform engineered to process multi- modal code queries (text and image) and generate comprehensive, structured outputs. The core innovation lies in a hybrid LLM Agent architecture that coordinates specialized tools, specifically Optical Character Recognition (OCR) for handling photographed code inputs and a Structured Output Generator for creating dynamic, animated flowcharts. The system deviates from using underpowered base models, advocating instead for the instruction fine- tuning of a high-performing yet resource- efficient model, such as the StarCoder2-3B model, utilizing Quantized Low-rank Adaptation (QLoRA).

Keywords

Large Language Models, Code Generation, Multi-Modality, Optical Character Recognition (OCR), Agentic Systems, Structured Output, QLoRA Fine-Tuning, Full- Stack Architecture, FastAPI, Perplexity UI.

Citations

IRE Journals:
Kunal Kumar Nath, Samridh Chauhan, Tanmay Jadhav, Pranit Virkar "Design and Implementation of a Multi-Modal, Agentic Code Companion System (ICC) using Fine-Tuned Code LLMs and Structured Visualization" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 659-669 https://doi.org/10.64388/IREV9I5-1711930

IEEE:
Kunal Kumar Nath, Samridh Chauhan, Tanmay Jadhav, Pranit Virkar "Design and Implementation of a Multi-Modal, Agentic Code Companion System (ICC) using Fine-Tuned Code LLMs and Structured Visualization" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1711930

APA:
Kunal Kumar Nath, Samridh Chauhan, Tanmay Jadhav, Pranit Virkar (2025). Design and Implementation of a Multi-Modal, Agentic Code Companion System (ICC) using Fine-Tuned Code LLMs and Structured Visualization. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1711930

MLA:
Kunal Kumar Nath, Samridh Chauhan, Tanmay Jadhav, Pranit Virkar "Design and Implementation of a Multi-Modal, Agentic Code Companion System (ICC) using Fine-Tuned Code LLMs and Structured Visualization" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1711930

BibTeX

@article{1711930,
author = {Kunal Kumar Nath, Samridh Chauhan, Tanmay Jadhav, Pranit Virkar},
title = {Design and Implementation of a Multi-Modal, Agentic Code Companion System (ICC) using Fine-Tuned Code LLMs and Structured Visualization},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {659-669},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1711930.pdf},
abstract = {This paper proposes the architectural design and implementation strategy for the Intelligent Code Companion (ICC) system, a novel platform engineered to process multi- modal code queries (text and image) and generate comprehensive, structured outputs. The core innovation lies in a hybrid LLM Agent architecture that coordinates specialized tools, specifically Optical Character Recognition (OCR) for handling photographed code inputs and a Structured Output Generator for creating dynamic, animated flowcharts. The system deviates from using underpowered base models, advocating instead for the instruction fine- tuning of a high-performing yet resource- efficient model, such as the StarCoder2-3B model, utilizing Quantized Low-rank Adaptation (QLoRA).},
keywords = {Large Language Models, Code Generation, Multi-Modality, Optical Character Recognition (OCR), Agentic Systems, Structured Output, QLoRA Fine-Tuning, Full- Stack Architecture, FastAPI, Perplexity UI.},
month = {November}
}