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@@ -383,7 +383,7 @@ If the model decides to call a tool it will define a `recipient` in the header o
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The model might also specify a `<|constrain|>` token to indicate the type of input for the tool call. In this case since it’s being passed in as JSON the `<|constrain|>` is set to `json`.
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```
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<|channel|>analysis<|message|>Need to use function get_weather.<|end|><|start|>assistant<|channel|>commentary to=functions.get_weather <|constrain|>json<|message|>{"location":"San Francisco"}<|call|>
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<|channel|>analysis<|message|>Need to use function get_current_weather.<|end|><|start|>assistant<|channel|>commentary to=functions.get_current_weather <|constrain|>json<|message|>{"location":"San Francisco"}<|call|>
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```
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#### Handling tool calls
@@ -399,7 +399,7 @@ A tool message has the following format:
} // namespace functions<|end|><|start|>user<|message|>What is the weather like in SF?<|end|><|start|>assistant<|channel|>analysis<|message|>Need to use function get_weather.<|end|><|start|>assistant<|channel|>commentary to=functions.get_weather <|constrain|>json<|message|>{"location":"San Francisco"}<|call|><|start|>functions.get_weather to=assistant<|channel|>commentary<|message|>{"sunny": true, "temperature": 20}<|end|><|start|>assistant
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} // namespace functions<|end|><|start|>user<|message|>What is the weather like in SF?<|end|><|start|>assistant<|channel|>analysis<|message|>Need to use function get_current_weather.<|end|><|start|>assistant<|channel|>commentary to=functions.get_current_weather <|constrain|>json<|message|>{"location":"San Francisco"}<|call|><|start|>functions.get_current_weather to=assistant<|channel|>commentary<|message|>{"sunny": true, "temperature": 20}<|end|><|start|>assistant
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```
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As you can see above we are passing not just the function out back into the model for further sampling but also the previous chain-of-thought (“Need to use function get_weather.”) to provide the model with the necessary information to continue its chain-of-thought or provide the final answer.
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As you can see above we are passing not just the function out back into the model for further sampling but also the previous chain-of-thought (“Need to use function get_current_weather.”) to provide the model with the necessary information to continue its chain-of-thought or provide the final answer.
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