Documentation on adapter train is lacking any details related to training on dataset with tool calling. And page about tool calling itself only explain how to use it from Swift without any internal details useful in training.
Question is how schema should looks like for including tool calling in dataset?
hii! looks like this is explained in the schema.md document included in the adaptor toolkit, see adapter_training_toolkit_v0_1_0.zip in docs/schema.md, specifically the section called Schema with instructions.
They talk about:
training.jsonl format for guided generationunfortunately it's not quite a tool calling example, but could you generate a well-formed data structure using guided generation that represents your tool call? You'd have to dispatch the actual call yourself in your business logic, but it's better than nothing...
alternatively if you're brave, you could consider looking at the patterns generated for tool calling by messing with base_model.pt and mimic that format, the framework is conceptually fairly simple
hope that helps?