78 lines
2.5 KiB
PHP
78 lines
2.5 KiB
PHP
<?php
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namespace App\Services\AI;
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use Illuminate\Support\Facades\Http;
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class OllamaProvider extends BaseAiProvider
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{
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public function getIdentifier(): string
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{
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return 'ollama';
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}
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public function generate(string $prompt, array $options = []): array
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{
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$baseUrl = $options['base_url'] ?? $this->config['base_url'] ?? 'http://localhost:11434';
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$model = $options['model'] ?? $this->config['default_model'] ?? 'llama3';
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$instruction = $options['instruction'] ?? $this->config['instruction'] ?? '';
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$startTime = microtime(true);
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try {
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$res = Http::timeout(120)->post("{$baseUrl}/api/generate", [
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'model' => $model,
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'prompt' => $instruction."\n\n".$prompt,
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'stream' => false,
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'options' => [
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'temperature' => (float) ($options['temperature'] ?? $this->config['temperature'] ?? 0.7),
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'num_predict' => (int) ($options['max_tokens'] ?? $this->config['max_tokens'] ?? 2000),
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],
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]);
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if ($res->failed()) {
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$error = 'Ollama Error: Make sure the server is running and the model is pulled.';
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$this->logUsage([
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'model' => $model,
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'prompt' => $prompt,
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'status' => 'failed',
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'error' => $error,
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]);
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return ['success' => false, 'error' => $error];
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}
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$data = $res->json();
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$response = $data['response'];
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$usage = [
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'prompt_tokens' => $data['prompt_eval_count'] ?? 0,
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'completion_tokens' => $data['eval_count'] ?? 0,
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'total_tokens' => ($data['prompt_eval_count'] ?? 0) + ($data['eval_count'] ?? 0),
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];
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$result = [
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'success' => true,
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'response' => $response,
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'usage' => $usage,
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'model' => $model,
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'latency' => microtime(true) - $startTime,
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];
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$this->logUsage([
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'model' => $model,
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'prompt' => $prompt,
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'response' => $response,
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'usage' => $usage,
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'status' => 'success',
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'metadata' => ['latency' => $result['latency']],
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]);
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return $result;
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} catch (\Exception $e) {
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return ['success' => false, 'error' => $e->getMessage()];
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}
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}
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}
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