Tool/function calling

Tool calling (also known as function calling) allows the LLM to request execution of functions you define. The model decides when to call a tool based on the conversation context.

Sequence: the application sends a chat request with tool definitions, the model answers with tool calls, the tool gate admits or denies each call, the application executes the admitted ones and returns their results, and the model produces the final answer. — One round of the bounded loop. The gate runs before the model is offered anything, and a call whose tool declares a write effect suspends the run for approval before it executes.

Defining tools

Example: Tool/function calling

$tools = [
    [
        'type' => 'function',
        'function' => [
            'name' => 'get_weather',
            'description' => 'Get current weather for a location',
            'parameters' => [
                'type' => 'object',
                'properties' => [
                    'location' => [
                        'type' => 'string',
                        'description' => 'City name',
                    ],
                    'unit' => [
                        'type' => 'string',
                        'enum' => ['celsius', 'fahrenheit'],
                    ],
                ],
                'required' => ['location'],
            ],
        ],
    ],
];

Executing tool calls

CompletionResponse::$toolCalls is a list of NetresearchNrLlmDomainValueObjectToolCall value objects — $toolCall->arguments is already a JSON-decoded associative array, so no manual json_decode() is needed. The two follow-up turns are built with the ChatMessage factories: ChatMessage::assistantToolCalls() echoes the assistant turn that carries the tool calls, and ChatMessage::toolResult() answers one call by its id.

Example: Handling tool call responses

use Netresearch\NrLlm\Domain\ValueObject\ChatMessage;

$response = $this->llmManager->chatWithTools($messages, $tools);

if ($response->hasToolCalls()) {
    // Echo the assistant turn (with all its tool calls) back first
    $messages[] = ChatMessage::assistantToolCalls($response->toolCalls, $response->content);

    foreach ($response->toolCalls as $toolCall) {
        // Execute your function — $toolCall->arguments is a decoded array
        $result = match ($toolCall->name) {
            'get_weather' => $this->getWeather($toolCall->arguments['location']),
            default => throw new \RuntimeException("Unknown function: {$toolCall->name}"),
        };

        // Answer the call by its id
        $messages[] = ChatMessage::toolResult($toolCall->id, json_encode($result, JSON_THROW_ON_ERROR));
    }

    // Ask the model to answer with the tool results in context
    $response = $this->llmManager->chat($messages);
}

Providers that implement toolcapableinterface support tool calling.