RubyLLM is a model client with Rails generators. Langchainrb is retrieval plumbing. Pick by whether you query your own documents, not by provider count.
Master RSpec testing for LangChain-Ruby with 25 working examples. Learn mocking, VCR, WebMock, and CI/CD automation. Build reliable AI features with 95%+ test coverage.
Building production LLM apps? Learn proven testing strategies for non-deterministic AI, LangSmith observability patterns, and monitoring frameworks that work. Complete guide with RSpec/pytest examples.
Complete LangGraph tutorial with working Python examples. Learn nodes, edges, checkpoints, human-in-the-loop, and map-reduce patterns. From first graph to production agent.
How to add memory to LangChain agents. Working Python examples for short-term, long-term, and entity memory. PostgreSQL and Redis persistence. Real production patterns.
Master LangChain architecture for production with Python. Complete guide with error handling, testing strategies, and working code examples for scalable AI agent systems.
Complete enterprise guide to scaling LangChain and CrewAI from prototype to production. Covers architecture patterns, security, compliance, monitoring, and real-world case study with 80% improvement metrics.
Learn proven strategies to reduce LLM costs substantially through token management, caching optimization, prompt engineering, and smart model selection. Practical examples with cost tracking included.
Learn LangChain Python with this comprehensive tutorial. Step-by-step guide with Django and FastAPI integration, production patterns, and 15+ working code examples. Build your first LLM app today.
Learn how to build AI-powered applications with LangChain-Ruby. Complete guide with working code examples, Rails integration, and production best practices for junior Ruby developers.
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