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1. llm-prompt-engineering-guide llm-prompt-engineering-guide Public

   Python 1

2. LLM-Drift-Observatory LLM-Drift-Observatory Public

   A hands-on framework for detecting and visualizing **behavioral drift** in Large Language Models (LLMs) across versions and providers.

   Jupyter Notebook

3. LLM-Scoring-Dashboard-Streamlit-OpenAI-eval-UI- LLM-Scoring-Dashboard-Streamlit-OpenAI-eval-UI- Public

   Streamlit-based interactive dashboard to evaluate LLM outputs on key qualitative metrics: Factuality Clarity Style

   Python 1

4. LLM-eval-benchmark-lab LLM-eval-benchmark-lab Public

   A modular, configurable benchmarking harness for evaluating LLM behavior across tasks, constraints, and model classes.

   Python 1

5. Prompt-Efficiency-Sandbox Prompt-Efficiency-Sandbox Public

   * Compare 3 versions of a prompt against: * GPT-3.5 * Mistral * QLoRA-based small model * Metrics: token usage, latency, eval score

   Jupyter Notebook 1

6. LLM-Evaluation-Toolkit LLM-Evaluation-Toolkit Public

   A practical toolkit for evaluating LLM outputs using GPT-based auto-grading. Designed for product teams to benchmark factuality, coherence, and tone in real-world use cases.

   Python 1