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Cohere Cost Optimization and Usage Tuning

cohere-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

Provides strategies to optimize costs when utilizing the Cohere API. This guide covers model tier selection (economy, standard, premium), implementing token budgets, reducing embedding storage costs (e.g., using int8), and establishing comprehensive usage trackers. It is essential for maintaining cost predictability in production AI deployments.

Deploying Cohere AI Apps to Cloud Platforms

cohere-deploy-integration

jeremylongshore/claude-code-plugins-plus-skills

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.

Setup Cohere SDK Authentication and Usage

cohere-install-auth

jeremylongshore/claude-code-plugins-plus-skills

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.

Migrating AI Integrations to Cohere

cohere-migration-deep-dive

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide provides a deep dive into migrating AI applications from major LLM providers (like OpenAI or Anthropic) to the Cohere platform. It covers critical technical steps, including API call adaptation, re-vectorizing embeddings, migrating tool definitions, and implementing the Adapter Pattern for seamless, gradual re-platforming of existing AI services.

Cohere API Performance Tuning Guide

cohere-performance-tuning

jeremylongshore/claude-code-plugins-plus-skills

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.

Cohere Production Deployment Checklist

cohere-prod-checklist

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive checklist guides the safe and robust deployment of Cohere API v2 integrations from staging to production. It covers critical steps including API key management, code quality standards, performance tuning, implementing health checks and circuit breakers, and defining full rollback procedures, ensuring mission-critical AI features are reliable for launch.

Cohere AI Application Architecture Guide

cohere-reference-architecture

jeremylongshore/claude-code-plugins-plus-skills

This detailed guide outlines a production-ready, layered architecture for building complex AI applications using the Cohere API v2. It covers implementing Retrieval-Augmented Generation (RAG) pipelines, advanced tool-use agents, and multi-model orchestration. Use this structure when designing new Cohere integrations or establishing robust architectural standards for enterprise AI solutions.

Cohere SDK Best Practices Patterns

cohere-sdk-patterns

jeremylongshore/claude-code-plugins-plus-skills

This guide provides production-ready code patterns for integrating with the Cohere AI API v2 using TypeScript and Python. It covers essential best practices, including singleton client management, robust retry mechanisms, type-safe chat wrappers, streaming, embedding, reranking, and structured JSON output. Use this when establishing team coding standards or refactoring existing Cohere integrations.

Cohere API V1 to V2 Migration Guide

cohere-upgrade-migration

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide details the necessary steps and breaking changes when migrating from Cohere API v1 to v2. It covers critical updates for SDKs (TypeScript/Python), including changes in chat message formats, role naming conventions, and required parameters for key endpoints like Embed, Rerank, and Tool Use, ensuring smooth API adoption.

Cohere Streaming Events and Connector Implementation

cohere-webhooks-events

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide demonstrates how to implement robust, real-time streaming UIs using Cohere's `chatStream` method. It details handling various event types, including content deltas, citation information for RAG, and structured tool call streams. A practical example is provided for creating a Server-Sent Events (SSE) endpoint, making it ideal for front-end integration with advanced AI features.

CoreWeave KServe GPU Inference Deployment

coreweave-core-workflow-a

jeremylongshore/claude-code-plugins-plus-skills

This guide details the process of deploying production-grade inference services on CoreWeave using KServe. It covers setting up autoscaling, GPU scheduling, and implementing scale-to-zero functionality for efficient ML model serving endpoints. Ideal for MLOps engineers deploying large language models (LLMs) or other complex AI models in a production environment.

CoreWeave GPU Cost Optimization Guide

coreweave-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide for optimizing cloud GPU expenditures on CoreWeave. Learn strategies like right-sizing instances, implementing scale-to-zero for development environments, and using quantization techniques (e.g., AWQ, GPTQ) to fit large models onto smaller, cost-effective GPUs, ensuring maximum efficiency and budget adherence for AI/ML workloads.

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