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pydantic-validation

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chirindaopensource / llm_faithfulness_hallucination_misalignment_detection

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End-to-End Python implementation of Semantic Divergence Metrics (SDM) for LLM hallucination detection. Uses ensemble paraphrasing, joint embedding clustering, and information-theoretic measures (JSD, KL divergence, Wasserstein distance) to quantify prompt-response semantic consistency. Based on Halperin (2025).

natural-language-processing information-theory scikit-learn statistical-analysis computational-linguistics python-implementation semantic-analysis ai-safety model-validation clustering-algorithms research-implementation openai-api prompt-engineering transformer-embeddings llm-evaluation hallucination-detection pydantic-validation robustness-testing divergence-metrics
  • Updated Aug 15, 2025
  • Jupyter Notebook

SayamAlt / Healthcare-AI-Clinical-Decision-Support-System-using-LangGraph

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Successfully developed a Healthcare AI Clinical Decision Support System, leveraging LangGraph, GPT-4o-mini, and PubMed to deliver real-time patient risk stratification, evidence-based treatment recommendations, and personalized clinical road maps with integrated drug safety validations.

pubmed-parser vector-database openfda-api streamlit-webapp pydantic-models prompt-engineering langchain retrieval-augmented-generation langgraph langchain-openai corrective-rag faiss-cpu agentic-workflow agentic-ai pydantic-validation langchain-community langgraph-tools tavily-search langchain-core langchain-text-splitters
  • Updated Feb 12, 2026
  • Python

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