Skill UI

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.

Automates comprehensive regression testing for all enabled cloud Large Language Model (LLM) providers. This includes verifying core connectivity, standard chat completion, structured JSON output, and Server-Sent Events (SSE) streaming capabilities. Essential for ensuring the reliability and stability of multi-cloud AI integrations in a CI/CD pipeline.

A comprehensive guide providing minimal working examples for core Cohere API v2 endpoints, including Chat completion, text embedding, and search reranking. This resource details basic setup, usage patterns, and includes runnable code examples in both TypeScript and Python, making it perfect for new AI integrations or learning advanced LLM functionality.

Implement professional text-to-speech generation and advanced voice cloning using the ElevenLabs API. This comprehensive workflow supports standard text-to-speech conversion, advanced voice customization (stability, similarity boost), and instant voice cloning from audio samples. It also includes WebSocket streaming for real-time applications like chatbots or live narration, making it ideal for building sophisticated, high-quality audio features.

A comprehensive guide to configuring robust CI/CD pipelines for Cohere API v2 applications. This skill covers setting up automated unit tests (mocked responses) and critical integration tests (real API calls) within environments like GitHub Actions. It ensures the stability and reliability of Cohere-powered features such as Chat, Embeddings, and Rerank across development cycles.

This comprehensive guide serves as a quick reference for diagnosing and resolving common Cohere API v2 errors and exceptions. It covers specific error codes (400, 429, 401, etc.), details the root causes, and provides actionable code fixes for various tasks, including Chat, Embed, and Rerank. Use this when debugging failed Cohere requests or encountering rate limits.

This comprehensive workflow guides the implementation of a complete Retrieval-Augmented Generation (RAG) pipeline using Cohere's core services. It demonstrates the full process: embedding documents, searching for relevant context, reranking results for precision, and finally generating a grounded answer with precise citations using the Chat API. Ideal for building knowledge-intensive, enterprise-grade Q&A systems.

Learn how to build complex, multi-step AI agents using Cohere's Chat API v2. This skill demonstrates defining external tools (like weather APIs or database searches) and implementing the full agent loop: model calls tool -> execute tool -> feed result back -> final answer. Ideal for creating autonomous, tool-using workflows that interact with external systems.

This skill provides robust mechanisms to ensure data privacy when interacting with Cohere APIs (Chat, Embed, etc.). It implements advanced PII detection (emails, SSNs, IP addresses, etc.), performs pre-call redaction to mask sensitive information, and includes post-call scrubbing and detailed audit logging. Essential for achieving GDPR/CCPA compliance and safely handling sensitive user data.

This skill provides comprehensive deployment guides for Cohere API v2 applications across major cloud platforms including Vercel, Fly.io, and Google Cloud Run. It covers critical aspects like secret management, setting up reliable health checks, optimizing performance, and implementing streaming chat endpoints to ensure production readiness.

This comprehensive guide details the process of installing and configuring the Cohere SDK (v2) in both Node.js and Python environments. It covers initial setup, setting API keys via environment variables, and provides full code examples for verifying connectivity across various Cohere endpoints, including Chat, Embed, and Rerank, enabling immediate integration into your AI projects.

A comprehensive guide for optimizing Cohere API v2 performance. Learn advanced strategies to improve throughput, reduce latency, and manage costs when using Chat, Embed, and Rerank endpoints. Techniques covered include dynamic model selection based on latency budgets, implementing streaming for faster perceived response times, efficient batch processing for embeddings, vector compression, and robust caching mechanisms.