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Recently, reports in the field of artificial intelligence regarding the ability of large models to generate formatted outputs have attracted attention. The related technology aims to enable large models to generate content precisely according to specific structures such as JSON, XML, or code formats, thereby reducing unstructured noise. Several technical communities and information platforms have noted that this feature is highly useful in automated data processing, API integration, and program development, effectively improving the efficiency of human-machine collaboration. Currently, mainstream open-source models are gradually integrating this capability, and some commercial applications are beginning to offer it as a standard service to meet users’ urgent need for high-quality, parsable output.
To meet the need for programs to obtain structured data, large models need to provide formatted output instead of simply returning natural language. The simplest way is to directly require the model to return JSON format in the prompt, but this method may result in the model returning JSON data in non-standard formats.