Practical pydantic validation decorators that support manual invocation. 支持手动调用的实用的pydantic验证装饰器。
A production-grade AIOps framework focused on model integrity and autonomous reliability. Features a LightGBM-driven multiclass inference engine via FastMCP, validated against data leakage through NMI analysis. Includes real-time Population Stability Index (PSI) drift monitoring and a closed-loop human-in-the-loop feedback system for sustainable ML
Framework Python para pipelines de ingestão de dados com arquitetura modular: conectores, validadores Pydantic, transformers e loaders (JSON, PostgreSQL) plugáveis.
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).
Analysing baby feeding data. Example data validation and transformation pipeline with interactive plotly dash application
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.
Url shortener api for the shrinklink project
Typed version of joblib's cache to work with pydantic validation and type checkers
A cloud-native Agentic AI assistant built with Streamlit and Gemini 2.5 Flash that processes natural language prompts into structured KYC payloads for automated IRCTC and TTD form injections via browser macro bookmarklets.
Event-driven pipeline for evaluating recruiting interviews (FastAPI, Redis Queue, PostgreSQL) with pluggable transcription (WhisperX / OpenAI), speaker diarization (Pyannote), structured LLM scoring via OpenRouter, and human-in-the-loop evidence validation.
Pydantic 中文文档
Defensive LLM Extraction Validation Middleware
Machine learning project that predicts a mental health score out of 10 using lifestyle and behavioral factors, with a FastAPI backend and simple frontend UI.
A production-ready full-stack machine learning web application that predicts student mental health scores based on social media usage, sleep, study habits, physical activity, and stress levels.
A chapter-wise Pydantic v2 reference guide with concise definitions and code examples for quick revision.
Showwright — compiles JSON show definitions into vMix broadcast presets
Transform CI/CD failure logs into real-time automated anomaly detection and root-cause classification using supervised machine learning.
To associate your repository with the pydantic-validation topic, visit your repo's landing page and select "manage topics."