In the Ollama API, you use the "tools" parameter to describe the available tools to the model, then use the "tool_calls" from the response to call the functions and send the results back to the model using "role": "tool".
Most of this is handled very easily by the ollama-python library, so you can integrate tool calling very simply in any script.
That said, this specific model was unable to call the functions and use the results in my "hello world" tests, so it seems it expects a few very specialized tools to be provided, which are defined by that platform they're advertising.
Right now the best tool calling model I've used is still qwen3, it works very reliably, and I can give it any ability I want and it'll use it when expected, even in /no_think mode.
Most of this is handled very easily by the ollama-python library, so you can integrate tool calling very simply in any script.
That said, this specific model was unable to call the functions and use the results in my "hello world" tests, so it seems it expects a few very specialized tools to be provided, which are defined by that platform they're advertising.
Right now the best tool calling model I've used is still qwen3, it works very reliably, and I can give it any ability I want and it'll use it when expected, even in /no_think mode.