Ollama Structured Outputs in 5 Minutes

About this video

Exploring Olama's New Structured Outputs In this video, I'm thrilled to announce that Olama now supports structured outputs, allowing you to constrain a model's output to a specific predefined JSON schema. This functionality is available in both the Olama Python and JavaScript libraries. I'll walk you through examples such as parsing data from documents, extracting data from images, and structuring language model responses with reliability and consistency. I'll also show you how to get started with Olama, how to install it, and how you can leverage libraries like Pydantic and Zod to define your schemas. Additionally, I'll touch on some advanced features like vision support and how Olama is compatible with the OpenAI SDK. 00:00 Introduction to Olama's Structured Outputs 00:36 Getting Started with Olama 01:11 Defining and Using JSON Schemas 01:58 Examples of Structured Outputs 02:10 Implementing Structured Outputs in Python and JavaScript 02:41 Data Extraction with OpenAI 03:14 Vision Capabilities in Olama 03:56 Integrating Olama with OpenAI SDK 04:39 Tips for Optimizing Structured Outputs