Skill UI

The official client library for interacting with Azure OpenAI services in .NET. It provides comprehensive access to various OpenAI models, including GPT-4o, embeddings, image generation (DALL-E), and audio transcription (Whisper). Use cases include building advanced chat applications, generating structured JSON outputs, and implementing Retrieval-Augmented Generation (RAG).

GPTQ enables post-training 4-bit quantization for large LLMs, delivering up to 4× memory reduction and 3-4× faster inference with under 2% perplexity loss on consumer GPUs through AutoGPTQ, PEFT, and Transformer integrations.

This guide provides a deep dive into migrating recruiting workflows from traditional tools to Juicebox. It covers key differences, such as switching from limited Boolean search to advanced Natural Language searching (PeopleGPT), expanding contact data, and integrating with over 41 ATS systems. Learn the step-by-step process for setting up your talent sourcing pipeline and optimizing your hiring process.

Knowledge Distillation is a crucial technique used to compress large, high-performing Language Models (Teacher) into smaller, more efficient Student models. This allows developers to deploy powerful AI capabilities (like those of GPT-4) on resource-constrained devices while significantly reducing inference costs. The method uses advanced techniques such as soft targets, temperature scaling, and Reverse KL Divergence (MiniLLM) to transfer knowledge effectively.

A comprehensive guide for migrating existing AI integrations from providers like OpenAI or Anthropic to Mistral AI. This blueprint covers the entire lifecycle: initial assessment of AI touchpoints, detailed model mapping (e.g., gpt-4o to mistral-large), implementing a provider-agnostic adapter pattern, and executing controlled, feature-flag-controlled rollout plans for major refactoring projects.

nanoGPT is a simplified, minimalist implementation designed specifically for educational purposes. It reproduces the core architecture of GPT-2 (124M) using clean, hackable code, allowing users to understand the entire transformer pipeline from scratch. The framework supports full workflows, including data preparation on various datasets (e.g., Shakespeare, OpenWebText), model training, and text generation, making it ideal for students and researchers learning NLP and deep learning principles.

Implements standardized function/tool calling across various large language models (LLMs) via OpenRouter. This unified approach allows developers to build sophisticated, multi-step agents and complex workflows, regardless of the underlying provider (e.g., GPT-4o, Claude 3.5). It simplifies the process of achieving structured output and tool-augmented reasoning in production systems.

This guide provides a comprehensive quickstart for integrating with OpenRouter, a unified endpoint for accessing multiple large language models (LLMs). It includes examples in cURL, Python, and TypeScript, demonstrating how to send chat completion requests, handle complex JSON responses, manage model parameters, and calculate usage cost across various providers (e.g., Llama, GPT-4o, Claude). Ideal for developers testing API connectivity or building multi-model applications.

This skill provides comprehensive tools to monitor the real-time availability, status, and performance of various large language models (LLMs) accessed via OpenRouter. It supports active health probes, catalog checks, and scheduled monitoring via Python and Bash, ensuring robust fault detection and failover logic for production systems that rely on external AI APIs.

This workflow provides an AI-powered platform for immersive conversation practice. It uses advanced language models (like GPT-4o) and real-time speech APIs to simulate real-life scenarios (e.g., ordering food, navigating). Users receive immediate, detailed feedback on pronunciation (phoneme level), grammar corrections, and vocabulary notes, making it an ideal core module for building language fluency and simulating professional tutoring experiences.

Provides a comprehensive incident response runbook for managing outages of the Speak API. It covers critical procedures including API triage, implementing offline fallback modes, and ensuring robust recovery steps. Ideal for DevOps teams maintaining language learning platforms reliant on real-time AI services (GPT-4o, Whisper).

This guide provides a comprehensive deep dive for migrating language learning platforms, covering everything from importing student progress to transitioning from legacy speech APIs. It details configuration using modern SDKs, integrating services like OpenAI's GPT-4o and Whisper, and includes verification steps. It is essential for managing complex platform migrations and ensuring a smooth operational transition.