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diff --git a/archive/2025/summer/bsc_gerg/README.md b/archive/2025/summer/bsc_gerg/README.md new file mode 100644 index 000000000..82e2e6e59 --- /dev/null +++ b/archive/2025/summer/bsc_gerg/README.md @@ -0,0 +1,43 @@ +# Terminology Agent System - Bachelor Thesis + +This thesis describes TAS (Terminology Agent System), a system based on the +architectural blackboard pattern and Generative AI (GenAI), integrating Large +Language Models (LLMs). TAS uses an event based system to coordinate various +Knowledge Sources (KS), which are responsible for text extraction, text normal- +ization, and definition generation. Its modular design enables the extension for +new algorithms and external data sources. + +## Getting started + +This project was built using python 3.11. First, install the projects dependencies using poetry: + +```shell +pip install poetry +poetry install +``` + +The system requires a valid OpenAI API key passed as environment variable: + +```shell +export OPENAI_API_KEY=<your-api-key> +``` + +TAS contains a simple fastapi interface. In order to start the server, run the following commands: + +```shell +pip install "fastapi[standard]" +fastapi dev src/main.py +``` + +## Tests + +In order to reproduce the test results from Appendix B, start the server and run the following commands: + +```shell +python -m unittest tests/test_definition.py +python -m unittest tests/test_extract.py +python -m unittest -v tests.test_integration.TestIntegrationTerminology.testExtractDomainTerminology_LLM +python -m unittest -v tests.test_integration.TestIntegrationTerminology.testExtractDomainTerminology +``` + +In order to run the performance evaluation, run the `test_performance.ipynb` jupyter notebook. \ No newline at end of file |