Ollama has introduced structured outputs, enhancing the way models can generate outputs by adhering to formats defined by JSON schemas. This update, available in both Python and JavaScript libraries, allows for more precise and reliable data extraction from documents, images, and language model responses. Users can now define a schema to structure the output, ensuring consistency across responses. The process involves updating to the latest Ollama library version, defining the desired output schema, and passing it to the model via the format parameter. This feature supports a wide range of applications, from parsing specific information from texts to extracting and structuring data from images with vision models and is available both via ollama native API and OpenAI API compatible endpoints.
Structured outputs promise to streamline tasks by providing data in a predefined format, making it easier to integrate and use in various applications. The update also hints at future enhancements, including performance improvements, GPU acceleration, and expanded format support. For developers and researchers, this means more control over output data, facilitating the development of more sophisticated and reliable AI-driven applications.
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