Skill UI

This skill provides a production-grade, containerized integration service for connecting to the Together AI platform. It facilitates high-performance inference, fine-tuning, and model deployment across over 100 open-source models using Together's OpenAI-compatible API. Includes comprehensive Docker setup, environment variable management, health checks, and zero-downtime rolling update strategies for robust, real-time LLM serving.

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.

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.

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.

Search over 2500 curated open-source repositories related to ChatGPT, LLMs, RAG, agents, and AI development. This skill helps users find tools, libraries, and frameworks by filtering categories, languages, or keywords. It relies on a bundled database rather than live web searches.

This skill automatically enriches research wiki pages that are left as bare scaffolds after initial ingestion. It reads multiple external sources (like arXiv/alphaxiv) and fills in 10 structured `_TODO._` sections (e.g., Problem/Gap, Key Results, Open Questions) with detailed prose summaries. Use this skill to transform incomplete research scaffolds into a comprehensive, structured knowledge base.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.

NVIDIA garak is an open-source LLM vulnerability scanner designed for comprehensive red-teaming and security assessment. It systematically probes large language models (via OpenAI-compatible APIs, Hugging Face, etc.) using thousands of adversarial prompts. It covers critical vulnerabilities such as prompt injection, jailbreaking, data leakage, and toxicity. Use this tool to establish a repeatable security baseline before or after deployment, validate the effectiveness of safety guardrails, or generate quantitative evidence for AI risk assessments.

Run open-source molecular design and structural biology tools on Tamarind Bio's managed cloud GPUs via REST API or MCP. Covers AlphaFold/Boltz/Chai structure prediction, RFdiffusion and ProteinMPNN design, antibody and nanobody engineering, DiffDock docking, binding affinity, MSA generation, and molecular dynamics — no local GPU setup needed.

The Neon AI Gateway provides a single API endpoint and one credential to access a diverse catalog of frontier and open-source LLMs (including OpenAI, Anthropic, Google Gemini, Meta, Alibaba, and DeepSeek). This unified layer simplifies integration by eliminating the need for separate provider accounts and managing model-specific SDK complexities. It allows developers to switch between models seamlessly by changing only the model name, while also providing crucial branch-scoped isolation for development and CI environments.

Pilot Protocol is an open-source overlay network providing AI agents with first-class network citizenship. It offers permanent virtual addresses, encrypted P2P communication, NAT traversal, and a structured app store. Use this skill when agents require stable networking across cloud changes, need direct, secure messaging without shared accounts, or must integrate structured external data services (e.g., live crypto prices) via local, typed capabilities.