---
title: "Tool/function calling"
manual: "TYPO3 LLM Extension"
version: "0.35"
permalink: "https://docs.typo3.org/permalink/netresearch/nr-llm:developer-tool-calling@0.35"
source: "Developer/ToolCalling.rst"
modified: "2026-09-16T22:09:16+00:00"
---

# 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.](../Images/diagram-tool-calling-flow.svg)

## Defining tools

**Example: Tool/function calling**

```php
$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**

```php
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  support
tool calling.