Skill UI

A production-ready Python SDK providing comprehensive patterns for integrating with the Kling AI API. This wrapper handles crucial operational complexities such as auto-refreshing JWT tokens, structured request/response models, exponential backoff polling for long-running tasks, and detailed error handling. Use this library when building stable, high-reliability applications that require advanced text-to-video or image-to-video synthesis capabilities.

This guide details how to apply sophisticated artistic styles and visual effects to Kling AI video generation. Users can achieve diverse aesthetics—such as Cinematic, Anime, Watercolor, or Cyberpunk—either through detailed prompt engineering or by utilizing the dedicated Effects API (e.g., hug, kiss). It also provides methods for pre-processing images using Kolors for highly consistent and professional video outputs.

Utilize the Kling AI API to generate high-quality, cinematic videos directly from descriptive text prompts. This advanced tool supports professional modes, camera movement control (pan, tilt, zoom), negative prompting, and synchronized native audio, making it ideal for professionals building robust text-to-video pipelines and creative content generation.

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 to mastering asynchronous programming using Kotlin Coroutines and Flow. Covers advanced topics such as structured concurrency, robust exception handling, and creating reactive data streams with StateFlow and SharedFlow. Essential for developing high-performance, modern Kotlin applications.

Provides deep expertise in modern Kotlin patterns, covering structured concurrency via Coroutines and Flow, Multiplatform architecture (KMP), declarative UI using Compose, and server implementation with Ktor. Ideal for building robust, type-safe, and highly maintainable applications across various platforms.

This guide provides comprehensive patterns and best practices for designing high-impact Key Performance Indicator (KPI) dashboards. It covers everything from establishing a KPI framework (Strategic, Tactical, Operational) to defining departmental metrics (Sales, Marketing, Finance) and implementing best-practice layouts for executive summaries and SaaS metrics. Use this skill to translate raw data into actionable business insights.

An expert guide for designing, implementing, and optimizing large-scale, secure, and highly available cloud-native infrastructure using Kubernetes. Covers advanced topics including GitOps workflows (ArgoCD/Flux), service mesh architecture (Istio), multi-cluster management, Policy as Code (OPA), and infrastructure automation with Terraform. Ideal for platform engineers building enterprise-grade container orchestration solutions.

This comprehensive guide details the end-to-end process of building Retrieval-Augmented Generation (RAG) pipelines using LangChain. It covers critical steps: loading diverse document types (PDF, CSV, TXT), splitting text into manageable chunks, generating high-quality embeddings (OpenAI), storing them in various vector databases (FAISS, Pinecone), and finally constructing the full runnable chain for accurate and context-aware querying.

A comprehensive runbook detailing standard operating procedures (SOPs) for managing production incidents involving LangChain and large language models (LLMs). It provides step-by-step guides for detecting, diagnosing, and mitigating common issues such as provider outages, high error rates, latency spikes, and excessive cost overruns. This skill is essential for DevOps and MLOps engineers maintaining LLM-powered applications.

This guide provides comprehensive techniques to optimize LangChain applications for production environments. Learn how to measure baseline latency, implement efficient caching strategies (in-memory, Redis, SQLite), utilize batch processing with concurrency control, and maximize perceived speed through streaming. Furthermore, it covers prompt optimization and strategic model selection to ensure high throughput and low costs.

This comprehensive guide details advanced strategies for building highly resilient applications that interact with external LLM APIs. It covers built-in exponential backoff retries, controlling request throughput via concurrency limits, implementing provider fallbacks, and custom rate limiting using token buckets. Essential knowledge for achieving stable, high-volume API usage in production systems.