add-ai

What problem does it solve?

It solves the chaos of adding LLM features to an existing project by standardizing model selection, Anthropic SDK wiring, prompt caching, and observability so integrations are reliable, cost-aware, and testable.

Core Features & Use Cases

• Model selection by use case: Chooses the right Claude model tier (latency/cost vs deep reasoning) via model-selector instead of guessing.
• Production-grade Anthropic SDK integration: Sets up the Anthropic client for chat, generation, tool use, structured outputs, and streaming patterns.
• Prompt caching by default: Enables prompt caching early to reduce latency and cost for repeated system prompts.
• LangSmith tracing + eval scaffolding: Adds tracing for runs and supports creating datasets + golden-example evals for regression testing.
• Use cases: Conversational chat, single-turn generation, RAG over knowledge bases, document analysis, image analysis orchestration, and agentic tool-enabled workflows.

Quick Start

Use add-ai when you want to add AI / LLM capabilities to your project, including Anthropic SDK wiring, model selection, prompt caching, and LangSmith tracing and evals.