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Tools & Function Calling

Tools (also known as function calling) empower your AI agents to interact with external systems, APIs, and data sources. This is a core capability for building agentic systems that can take actions beyond generating text.

Overview

When you provide tools to an AI agent, the model can:

  1. Decide when a tool is needed to answer a query
  2. Select the appropriate tool
  3. Generate the correct input parameters
  4. Receive the tool's output
  5. Incorporate the results into its response

Defining Tools

Use CallbackToolDefinition to define tools with callback functions:

<?php
use Soukicz\Llm\Tool\CallbackToolDefinition;

$tool = new CallbackToolDefinition(
    name: 'tool_name',
    description: 'Clear description of what the tool does and when to use it',
    inputSchema: [
        'type' => 'object',
        'properties' => [
            'param1' => ['type' => 'string', 'description' => 'Parameter description'],
            'param2' => ['type' => 'number', 'description' => 'Another parameter'],
        ],
        'required' => ['param1'],
    ],
    handler: function (array $input) {
        // Your tool logic here
        return $result;
    }
);

Complete Example: Currency Converter Agent

<?php
use GuzzleHttp\Client;
use GuzzleHttp\Promise\PromiseInterface;
use GuzzleHttp\Psr7\Response;
use Soukicz\Llm\Cache\FileCache;
use Soukicz\Llm\Client\Anthropic\AnthropicClient;
use Soukicz\Llm\Client\Anthropic\Model\AnthropicClaude45Sonnet;
use Soukicz\Llm\Client\LLMAgentClient;
use Soukicz\Llm\Message\LLMMessage;
use Soukicz\Llm\Message\LLMMessageContents;
use Soukicz\Llm\LLMConversation;
use Soukicz\Llm\LLMRequest;
use Soukicz\Llm\Tool\CallbackToolDefinition;

require_once __DIR__ . '/vendor/autoload.php';

$cache = new FileCache(sys_get_temp_dir());
$anthropic = new AnthropicClient('sk-xxxxxx', $cache);
$agentClient = new LLMAgentClient();

$currencyTool = new CallbackToolDefinition(
    name: 'currency_rates',
    description: 'Tool for getting current currency rates. Required input is currency code of source currency and currency code of target currency.',
    inputSchema: [
        'type' => 'object',
        'properties' => [
            'source_currency' => ['type' => 'string'],
            'target_currency' => ['type' => 'string'],
        ],
        'required' => ['source_currency', 'target_currency'],
    ],
    handler: function (array $input): PromiseInterface {
        $client = new Client();

        // Tool can return either a promise or a value
        return $client->getAsync('https://cdn.jsdelivr.net/npm/@fawazahmed0/currency-api@latest/v1/currencies/' . strtolower($input['source_currency']) . '.json')
            ->then(function (Response $response) use ($input) {
                $data = json_decode($response->getBody()->getContents(), true, 512, JSON_THROW_ON_ERROR);

                return LLMMessageContents::fromArrayData([
                    'rate' => $data[strtolower($input['source_currency'])][strtolower($input['target_currency'])],
                ]);
            });
    }
);

$response = $agentClient->run(
    client: $anthropic,
    request: new LLMRequest(
        model: new AnthropicClaude45Sonnet(AnthropicClaude45Sonnet::VERSION_20250929),
        conversation: new LLMConversation([
            LLMMessage::createFromUserString('How much is 100 USD in EUR today?')
        ]),
        tools: [$currencyTool],
    )
);

echo $response->getLastText();

Tool Handler Return Types

Tool handlers must return either:

  1. LLMMessageContents - Structured response data (recommended)
  2. Promises - For async operations (recommended for API calls)
<?php
// LLMMessageContents (recommended for synchronous operations)
handler: function (array $input): LLMMessageContents {
    return LLMMessageContents::fromArrayData(['key' => 'value']);
}

// Promise (recommended for async operations like API calls)
handler: function (array $input): PromiseInterface {
    return $httpClient->getAsync($url)
        ->then(function ($response) {
            $data = json_decode($response->getBody(), true);
            return LLMMessageContents::fromArrayData($data);
        });
}

Note: Tool handlers cannot return plain arrays or scalar values. Always wrap your results in LLMMessageContents::fromArrayData().

Tip: If you need to convert LLMMessageContents back to a plain array (e.g., for testing), use the toArray() method:

<?php
$result = $tool->handle(['input' => 'value']);
$array = $result->toArray();  // Converts to plain array

Built-in Tools

Text Editor Tool

For building file-manipulation agents with Anthropic models, you can use the TextEditorTool. This tool requires a custom storage implementation.

Note: This is an advanced feature that requires implementing the TextEditorStorage interface to handle file operations securely.

<?php
use Soukicz\Llm\Tool\TextEditor\TextEditorTool;
use Soukicz\Llm\Tool\TextEditor\TextEditorStorage;

// You need to implement TextEditorStorage interface
class MyTextEditorStorage implements TextEditorStorage {
    public function __construct(private string $basePath) {}

    public function read(string $path): string {
        // Implement secure file reading
        return file_get_contents($this->basePath . '/' . $path);
    }

    public function write(string $path, string $content): void {
        // Implement secure file writing
        file_put_contents($this->basePath . '/' . $path, $content);
    }

    // Implement other required methods...
}

$storage = new MyTextEditorStorage('/path/to/working/directory');
$textEditorTool = new TextEditorTool($storage);

$request = new LLMRequest(
    model: new AnthropicClaude45Sonnet(AnthropicClaude45Sonnet::VERSION_20250929),
    conversation: new LLMConversation([
        LLMMessage::createFromUserString('Create a new file called hello.txt with "Hello World"')
    ]),
    tools: [$textEditorTool],
);

The text editor tool supports:

  • view - View file contents
  • create - Create new files
  • str_replace - Replace text in files
  • insert - Insert text at specific line numbers

Security Considerations: When implementing TextEditorStorage, ensure proper path validation, access controls, and sandboxing to prevent unauthorized file access.

Input Schema

The inputSchema follows JSON Schema specification. Common patterns:

Simple Parameters

<?php
'inputSchema' => [
    'type' => 'object',
    'properties' => [
        'query' => ['type' => 'string', 'description' => 'Search query'],
        'limit' => ['type' => 'integer', 'description' => 'Max results'],
    ],
    'required' => ['query'],
]

Enums

<?php
'properties' => [
    'priority' => [
        'type' => 'string',
        'enum' => ['low', 'medium', 'high'],
        'description' => 'Task priority level'
    ],
]

Arrays

<?php
'properties' => [
    'tags' => [
        'type' => 'array',
        'items' => ['type' => 'string'],
        'description' => 'List of tags'
    ],
]

Nested Objects

<?php
'properties' => [
    'location' => [
        'type' => 'object',
        'properties' => [
            'lat' => ['type' => 'number'],
            'lng' => ['type' => 'number'],
        ],
        'required' => ['lat', 'lng'],
    ],
]

Best Practices

  1. Clear Descriptions - Provide detailed descriptions for both the tool and each parameter
  2. Use Promises for I/O - Return promises for async operations like API calls
  3. Validate Input - The schema helps, but add runtime validation if needed
  4. Error Handling - Handle errors gracefully and return meaningful error messages
  5. Keep Tools Focused - One tool should do one thing well
  6. Document Side Effects - If a tool modifies state, make it clear in the description

Provider Support

  • ✅ Anthropic (Claude) - Full support, including native tools
  • ✅ OpenAI (GPT) - Full function calling support
  • ✅ Google Gemini - Full function calling support
  • ⚠️ OpenAI-compatible - Depends on the underlying model

See Also