Building AI powered features into Ruby on Rails applications has become increasingly common, but the development process can quickly become expen$ive and cumbersome when you’re constantly hitting external APIs during testing and iteration. Every debug session, feature experiment, and streaming test can rack up costs while you wait for network requests to complete. This is where Ollama becomes an amazing tool for web / Rails developers.

Ollama transforms your development workflow by allowing you to run powerful AI models like Deepseek-r1 and Gemma directly on your local machine. The setup process is simple: Ollama handles the heavy lifting of downloading and configuring these models, then spins up a local server that exposes an OpenAI SDK-compatible API. This means you can drop Ollama into your existing Rails application with minimal code changes, simply by pointing your API calls to localhost instead of expensive external services.

Performance benefits are immediately noticeable. While smaller models available through Ollama might not match the capabilities of their cloud-hosted counterparts, they’re surprisingly capable for development work. They respond quickly without network latency, making them perfect for rapid prototyping and debugging turbostream implementations. You can iterate on prompts, test edge cases, and experiment with different approaches without worrying about API quotas or token costs.

This local-first approach also enhances your development workflow in other ways: You can work offline, test with sensitive data without external transmission concerns, and maintain consistent performance regardless of your internet connection. The seamless integration with existing OpenAI SDK patterns means your production code remains unchanged while your development environment becomes more efficient and cost-effective.

For Rails developers venturing into AI integration, Ollama offers the perfect balance of convenience, performance, and economics for local development, allowing you to focus on building great features rather than managing API costs and network dependencies. Give it a shot and let me know what your own personal workflow is!