Skill UI

This guide teaches developers how to implement robust, event-driven architecture patterns with the Anthropic Claude API. It covers two key methods: Server-Sent Events (SSE) for real-time streaming responses, and the Message Batches API for high-volume, asynchronous bulk processing. Use this when building real-time chat features or processing large datasets offline.

A comprehensive guide detailing five robust architectural patterns for building applications powered by Claude, including Chatbot, RAG, Agent, Content Pipeline, and Evaluation. It provides complete code examples and decision matrices to help developers select the optimal architecture based on project requirements, cost, and complexity.

This guide provides comprehensive, step-by-step instructions for installing and authenticating the Anthropic SDK. It covers setup for both Python and Node.js environments, detailing how to securely configure API keys using environment variables. Essential for developers starting new projects that integrate with Claude models.

A comprehensive troubleshooting guide for Abridge clinical documentation integration. Covers common errors in authentication, EHR connectivity, audio streaming, note generation, and FHIR validation. Essential for developers and technical users debugging AI-powered clinical workflows.

A comprehensive checklist designed to ensure Claude-powered applications are robust, secure, and production-ready before going live. It guides developers through critical areas, including robust error handling, API security best practices, cost control mechanisms, real-time monitoring setup, and performance optimization, ensuring a stable user experience.

This skill provides advanced techniques for robust prompt engineering within LangChain applications. It solves common production issues, such as f-string template breakage when user input contains literal curly braces, and guides developers on consolidating scattered prompts. Crucially, it details how to use the LangSmith Prompt Hub to version, pin, and A/B test prompts using immutable commit hashes, ensuring stable, reproducible LLM deployments.

This guide provides a comprehensive workflow for generating cinematic AI videos using Runway's Gen-3 Alpha model via the Python SDK. It covers the entire process from text-to-video task creation, polling for task completion status, to successfully downloading the final high-quality video output. Ideal for developers integrating advanced creative video generation into their applications.

This guide provides detailed, step-by-step instructions for installing and authenticating the Runway ML SDK. It covers prerequisites for both Python and Node.js environments, including setting up API keys and verifying the connection. This setup is essential for developers who plan to perform high-fidelity AI video generation, image editing, or advanced creative content workflows using the Runway platform.

This guide details performance tuning and implementation patterns for the RunwayML platform. It provides a practical Python SDK pattern for advanced AI tasks, including image-to-video conversion and generating high-quality creative content using various models like gen3a_turbo. Ideal for developers integrating creative AI capabilities into their applications.

This guide provides a comprehensive tutorial on running various AI inference tasks using the Together AI API, which is compatible with the OpenAI standard. It demonstrates key functionalities including chat completions, streaming responses, image generation, and creating embeddings. This is ideal for developers who need to test open-source models, compare performance across different LLMs (like Llama or Mixtral), or integrate powerful generative AI features into their applications using Python or Node.js.

This guide provides comprehensive instructions for setting up and authenticating the Together AI SDK. It covers installation using both Python and Node.js, configuring the necessary API key, and verifying connectivity to utilize the OpenAI-compatible API for powerful open-source model inference and fine-tuning tasks. Ideal for developers starting with Together AI.

This guide provides detailed instructions for optimizing cost and implementing voice-to-text API integrations using Wispr Flow. It covers best practices for WebSocket streaming, REST API usage, context awareness (like programming code), and robust error handling, helping developers build advanced voice-powered applications.