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unshDee/README.md

Ansh Dawda

MSc Data Science & AI @ UdS. Werkstudent at DHC

I build RAG systems and LLM pipelines mostly — retrieval, evaluation, knowledge graphs

anshdawda.me · Saarbrücken, Germany

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  1. proofrag proofrag Public

    Point your agent at your docs and your RAG app; get a golden test set + an LLM-as-judge & retrieval scorecard, in one command.

    Python 2

  2. rag-utils rag-utils Public

    Reusable utilities for RAG pipelines: chunking strategies, embedding wrappers, retrieval evaluation helpers.

    Python

  3. FactCheckLIAR FactCheckLIAR Public

    Fact-verification pipeline with hybrid BM25 + dense retrieval on the LIAR misinformation dataset. Streamlit interface for real-time claim checking.

    Python

  4. sampler-scope sampler-scope Public

    How much of an LLM agent’s apparent behavior comes from the decoder rather than the model alone? SamplerScope holds the model’s logits fixed, changes only the decoding method, and measures how this…

    Python