Skill UI

Provides comprehensive guidance for performance tuning, inference, and fine-tuning using the Together AI platform. This skill supports working with Together AI's OpenAI-compatible API, covering model deployment, utilizing various open-source models (like Llama, Mixtral), and implementing best practices for efficient and cost-effective batch inference.

This comprehensive checklist guides the operational setup (MLOps) for AI applications using Together AI's OpenAI-compatible API. It covers critical production concerns, including secure API key management, implementing robust rate limit handling, building error resilience features (circuit breakers, exponential backoff), and setting up comprehensive monitoring for latency, cost control, and model availability. Essential for reliable, scalable LLM deployment.

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

A comprehensive guide to implementing production-ready patterns for interacting with the Together AI API. This includes a singleton client for seamless OpenAI-compatible integration, robust error wrappers with retry logic, and a fluent request builder. It covers best practices for LLM inference, model setup, and handling diverse response types (chat, embedding, fine-tuning).

This guide provides comprehensive strategies for migrating applications using the Together AI platform. It addresses common issues like model ID deprecations, API schema changes (for fine-tuning or chat completions), and best practices for robust inference and deployment using their OpenAI-compatible API.

This utility handles asynchronous webhook events from Together AI, enabling developers to build robust, event-driven Machine Learning pipelines. Instead of constantly polling the API for status updates (e.g., fine-tuning completion, batch job status, model deprecation), you can subscribe to these webhooks. It includes logic for signature verification, event routing, and idempotency, making it ideal for mission-critical AI workflows.

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.

This skill provides real-time object detection capabilities by leveraging the Google Coral Edge TPU accelerator. It operates natively within Windows Subsystem for Linux (WSL), allowing high-speed, low-latency inference on live camera frames. By utilizing hardware acceleration, it achieves impressive performance (e.g., ~4ms inference at 320x320), making it ideal for edge computing projects requiring rapid visual analysis and resource efficiency.

Utilize Gemini's advanced AI capabilities for broad and comprehensive literature discovery. Unlike traditional keyword-based APIs (like arXiv or Semantic Scholar), this tool decomposes research topics into multiple angles, aliases, and sub-problems, providing a deep, multi-faceted survey of academic literature, including code availability and recent preprints.

This command runs a high-stakes business memo through multiple advanced AI models (Claude, Codex, Gemini) to achieve a robust consensus review. It identifies areas of agreement, divergence, and critical concerns, providing an independent sanity check before irreversible corporate decisions like M&A, fundraises, or major pivots. It includes graceful degradation for API availability.

This skill utilizes the 2slides API to generate professional, multi-format presentations. It supports creating slides from raw text, summarizing uploaded documents, matching a specific style from a reference image, and adding AI voice narration. Outputs include interactive slide URLs and downloadable PDFs. Ideal for any 'make slides' or 'create a deck' workflow.

This meta-skill automates the entire process of creating a professional, high-quality AI short drama video from a simple topic or prompt. It intelligently drafts a shot-by-shot shooting script, maintains character and scene consistency across all shots, generates comprehensive visual assets (identity reference, per-shot compositions), and compiles the final MP4 with burned subtitles and title cards. Suitable for content creators, marketers, and storytellers needing rapid, consistent visual narratives.