Skill UI

This comprehensive guide teaches you how to integrate and use the ElevenLabs Text-to-Speech (TTS) API. It provides multiple code examples (TypeScript, Python, cURL) for generating high-quality speech audio from text. Learn advanced features such as detailed voice parameter control, choosing optimal models (e.g., streaming vs. standard), and implementing low-latency streaming for real-time applications.

This comprehensive guide provides a production-grade reference architecture for building robust Text-to-Speech (TTS) and voice applications using the ElevenLabs API. It covers detailed project structure, service layer design (including TTS orchestration, voice management, and caching), configuration handling, and best practices for streaming and multi-model orchestration, ensuring scalability and reliability in a commercial SaaS environment.

This utility enables multi-camera streaming by converting standard camera protocols (RTSP, RTMP, HTTP) into low-latency WebRTC streams using the go2rtc sidecar. It is essential for building real-time surveillance dashboards, live video monitoring systems, or integrating diverse IP cameras into a single web interface.

Master advanced techniques for optimizing API interactions with HubSpot. Learn to implement batch operations, utilize effective caching strategies (e.g., LRU), minimize property requests, and handle large datasets via efficient pagination and streaming. This skill dramatically improves throughput and reduces API call latency across CRM operations.

This guide addresses critical LangGraph streaming pitfalls, including state overdraw, proxy buffering issues (Nginx, Cloud Run), and excessive event noise. It provides a production-grade pattern for implementing robust SSE/WebSocket endpoints using FastAPI. Learn how to correctly select the `stream_mode` (messages, updates, values) and implement server-side event filtering to reliably build live-token chat UIs and perform comprehensive state visualization.

A comprehensive guide to advanced, production-ready LLM inference using LangChain 1.0. This skill addresses common pitfalls and bugs when integrating multiple providers (Claude, GPT-4o, Gemini), covering issues like structured output reliability, correct streaming token accounting, and robust handling of complex AIMessage content blocks. It teaches best practices for model initialization, provider routing, and version-safe code implementation.

Use this skill to set up real-time monitoring of on-chain events using QuickNode Streams. It allows developers to define custom filters for specific contracts or topics (e.g., ERC-20 transfers) and automatically receive processed events via a dedicated webhook endpoint. This is ideal for building decentralized applications (dApps) that require immediate and reliable knowledge of blockchain activity.

Master advanced techniques for optimizing Salesforce API interactions. This guide covers optimizing SOQL queries using selective fields and indexed WHERE clauses. It details methods to minimize API calls by utilizing Collections and Composite APIs, implementing metadata caching, and efficiently streaming large result sets via Bulk API 2.0, ensuring stable and high-performance integrations.

This skill guides the implementation of robust, real-time data integrations with Salesforce. It covers three critical mechanisms: Change Data Capture (CDC) for tracking record changes, Platform Events for custom business event buses, and handling Outbound Messages. Learn how to build resilient, event-driven architectures using asynchronous streaming protocols and ensure idempotent event processing.

This guide provides production-ready, idiomatic patterns for interacting with Snowflake using official SDKs (Node.js and Python). It covers essential patterns like implementing robust connection pooling, handling asynchronous query wrappers, efficiently streaming large result sets, and utilizing context managers for reliable resource cleanup. Use this when establishing team coding standards or optimizing data access performance.

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.

Provides comprehensive guidelines for integrating the Wispr Flow voice-to-text API into development environments. This skill covers both low-latency WebSocket streaming and simpler REST endpoint usage. It is essential for building voice-powered applications, including real-time dictation, command-line interactions, and context-aware code transcription across multiple platforms (Mac, Windows, iOS).