My first query:
> Make it a little warmer in here.
The reply:
> "name": "set_thermostat", > "arguments": { > "temperature": 65, > "mode": "cool", > ... > "reasoning": "'warmer' implies need for cooling; set_thermostat with temperature 65 (typical warmth) and mode 'cool'.",
Maybe I'm doing it wrong?
loading story #49254221
It's not a conversational model. It's meant as a local tool calling model.
Yes, I think OP understands that. What he and many others in this thread are trying to understand is what makes this model useful.
Turning a voice command into a tool call should be self evidently useful, being able to do that on a small embedded device is the novelty here. In this theoretical example, the thermostat is hosting the model on device and would use no external services.
I confused by the dispatch model. Tool calls typically need some reasonability to be deterministic and, more importantly, predictable in response (o/w GIGO). Why would the thermostat need to interpret a voice command that the node capturing the voice command would not interpret instead?
loading story #49253309
That's exactly what they were testing and what it failed at
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Yes, and it seems the tool called here was the thermostat, to set the mode literally the opposite of what was requested.
"Make it warmer"
tool that cools room called
Try asking it to set the thermostat to a value. It's a very small model, there's not much reasoning capability