From JSON to the Cloud: An AI Dashboard with Streamlit and GitHub Actions
Elegir un modelo de inteligencia artificial para procesar documentos implica responder tres preguntas: ¿qué tan bien resuelve la tarea?, ¿cuánto cuesta? y ¿cuánto tarda? Para explorar esas decisiones desarrollé ModelScope AI , un dashboard con Python, Streamlit y Plotly. La aplicación compara resultados de modelos dentro de una misma tarea, idioma y formato de entrada. Enlaces del proyecto Código…
A developer has created ModelScope AI, a dashboard that compares the performance of artificial intelligence models in processing documents. The dashboard, built with Python, Streamlit, and Plotly, allows users to evaluate models based on accuracy, cost, and response time for specific tasks, languages, and input formats. The dashboard uses data from ModelVerdict, a public JSON dataset that provides results for tasks such as invoice extraction, email classification, and document summarization.
The developer has made the code and deployed application publicly available on GitHub and Streamlit Community Cloud.
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