ls1intum/edutelligence
Jul 2025 – Jul 2025
1 Month active
Languages Used
HTMLJavaScriptPython
Technical Skills
API IntegrationData ScienceData VisualizationMachine LearningTestingWeb Development
Tobias Wasner
PROFILE
Tobias Wasner
Tobias Wasner developed an end-to-end Model Data Preparation and Cross-Model Comparison Toolkit for the ls1intum/edutelligence repository, focusing on automating data preparation and comparative analysis across AI models. Using Python, JavaScript, and HTML, he built a module that prepares model data, sends cross-model requests to Azure and OpenWebUI, retrieves results by ID, and generates HTML reports for side-by-side model evaluation. He updated the test_complete.ipynb notebook to demonstrate the full workflow, including model setup, prompt classification, task scheduling, and result submission. This work provided a unified, reproducible process for evaluating and comparing model responses, enhancing the repository’s analytical capabilities.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
37,850
Activity Months1
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 — ls1intum/edutelligence: Implemented end-to-end Model Data Preparation and Cross-Model Comparison Toolkit, enabling automated data preparation, cross-model requests to Azure and OpenWebUI, retrieval of model data by ID, and generation of an HTML comparison report. Updated test_complete.ipynb to demonstrate the full workflow: model setup, prompt classification, task scheduling, and result submission to Azure/OpenWebUI, culminating in a unified model-response report. Merged Logos PR into main to consolidate changes and unlock the new toolkit.
1 Commits • 1 Features
Jul 1, 2025July 2025 — ls1intum/edutelligence: Implemented end-to-end Model Data Preparation and Cross-Model Comparison Toolkit, enabling automated data preparation, cross-model requests to Azure and OpenWebUI, retrieval of model data by ID, and generation of an HTML comparison report. Updated test_complete.ipynb to demonstrate the full workflow: model setup, prompt classification, task scheduling, and result submission to Azure/OpenWebUI, culminating in a unified model-response report. Merged Logos PR into main to consolidate changes and unlock the new toolkit.
July 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
HTMLJavaScriptPython
Technical Skills
API IntegrationData ScienceData VisualizationMachine LearningTestingWeb Development
Repositories Contributed To
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