Optoelectronic thin films play a critical role across various high-tech industries, including new materials, energy storage sectors, chip manufacturing, and biomedicine. This paper details the enhancement of optoelectronic thin film properties through the innovative use of Sum Frequency Generation (SFG) spectroscopy. This non-linear spectroscopic technique is uniquely suited to studying film surfaces and interfaces without damaging the samples, offering detailed insights into molecular arrangements and chemical states at these critical junctures. Further, this study introduces a novel Python based application developed using the PyQt5 framework, which is designed to efficiently handle and analyze spectroscopic data. The application incorporates advanced data processing functions such as data denoising, Fourier transformation, square wave matrix extraction, inverse Fourier transformation, and data integration, providing a comprehensive tool for researchers. Our results demonstrate significant improvements in the precision and efficiency of data analysis, leading to enhanced performance and quality of optoelectronic films. The integration of interdisciplinary technological approaches with advanced programming techniques and mathematical analysis through SFG spectroscopy underscores its potential to revolutionize the field by providing a more precise characterization of the material's microstructural features and advancing the development and optimization processes of optoelectronic thin film technology.