refactor: extract AbstractLlmPredictionProvider for shared boilerplate
Anthropic, Gemini, and OpenAi providers each repeated: API-key gate, chronological price-list building, response validation (direction/confidence/reasoning), TrendDirection::tryFrom, confidence cap at 85, and the top-level try/catch + Log::error. Now in AbstractLlmPredictionProvider: - LLM_MAX_CONFIDENCE constant - buildPriceList(Collection) helper - buildPrediction(input, ?source) — handles direction validation, confidence cap, model construction - defaultPrompt(priceList) — shared by Gemini and OpenAi - Default predict() flow (apiKey + callProvider + buildPrediction + try/catch). Gemini and OpenAi only implement apiKey() and callProvider(). Anthropic overrides predict() because of its multi-phase web-search + forced-tool flow but reuses the helpers. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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@@ -2,112 +2,61 @@
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namespace App\Services\LlmPrediction;
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use App\Enums\PredictionSource;
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use App\Enums\TrendDirection;
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use App\Models\BrentPrice;
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use App\Models\PricePrediction;
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use App\Services\ApiLogger;
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use Illuminate\Support\Collection;
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use Illuminate\Support\Facades\Http;
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use Illuminate\Support\Facades\Log;
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use Throwable;
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class OpenAiPredictionProvider implements OilPredictionProvider
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class OpenAiPredictionProvider extends AbstractLlmPredictionProvider
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{
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private const int LLM_MAX_CONFIDENCE = 85;
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public function __construct(
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private readonly ApiLogger $apiLogger,
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) {}
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public function predict(Collection $prices): ?PricePrediction
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protected function apiKey(): ?string
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{
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if (! config('services.openai.api_key')) {
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return null;
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}
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$priceList = $prices->sortBy('date')
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->map(fn (BrentPrice $p) => $p->date->toDateString().': $'.$p->price_usd)
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->implode("\n");
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return config('services.openai.api_key');
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}
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protected function callProvider(string $apiKey, string $priceList): ?array
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{
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$url = 'https://api.openai.com/v1/chat/completions';
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try {
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$response = $this->apiLogger->send('openai', 'POST', $url, fn () => Http::timeout(15)
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->withToken(config('services.openai.api_key'))
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->post($url, [
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'model' => config('services.openai.model', 'gpt-4o-mini'),
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'response_format' => [
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'type' => 'json_schema',
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'json_schema' => [
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'name' => 'oil_prediction',
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'strict' => true,
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'schema' => [
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'type' => 'object',
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'properties' => [
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'direction' => ['type' => 'string', 'enum' => ['rising', 'falling', 'flat']],
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'confidence' => ['type' => 'integer'],
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'reasoning' => ['type' => 'string'],
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],
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'required' => ['direction', 'confidence', 'reasoning'],
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'additionalProperties' => false,
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$response = $this->apiLogger->send('openai', 'POST', $url, fn () => Http::timeout(15)
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->withToken($apiKey)
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->post($url, [
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'model' => config('services.openai.model', 'gpt-4o-mini'),
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'response_format' => [
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'type' => 'json_schema',
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'json_schema' => [
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'name' => 'oil_prediction',
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'strict' => true,
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'schema' => [
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'type' => 'object',
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'properties' => [
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'direction' => ['type' => 'string', 'enum' => ['rising', 'falling', 'flat']],
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'confidence' => ['type' => 'integer'],
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'reasoning' => ['type' => 'string'],
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],
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'required' => ['direction', 'confidence', 'reasoning'],
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'additionalProperties' => false,
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],
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],
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'messages' => [[
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'role' => 'user',
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'content' => $this->prompt($priceList),
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]],
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]));
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],
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'messages' => [[
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'role' => 'user',
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'content' => $this->defaultPrompt($priceList),
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]],
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]));
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if (! $response->successful()) {
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Log::error('OpenAiPredictionProvider: request failed', ['status' => $response->status()]);
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return null;
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}
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$data = json_decode($response->json('choices.0.message.content') ?? '{}', true);
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if (! isset($data['direction'], $data['confidence'], $data['reasoning'])) {
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Log::error('OpenAiPredictionProvider: unexpected response format', ['data' => $data]);
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return null;
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}
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$direction = TrendDirection::tryFrom($data['direction']);
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if ($direction === null) {
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Log::error('OpenAiPredictionProvider: invalid direction', ['direction' => $data['direction']]);
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return null;
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}
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return new PricePrediction([
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'predicted_for' => now()->toDateString(),
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'source' => PredictionSource::Llm,
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'direction' => $direction,
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'confidence' => min((int) $data['confidence'], self::LLM_MAX_CONFIDENCE),
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'reasoning' => $data['reasoning'],
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'generated_at' => now(),
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]);
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} catch (Throwable $e) {
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Log::error('OpenAiPredictionProvider: predict failed', ['error' => $e->getMessage()]);
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if (! $response->successful()) {
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Log::error(self::class.': request failed', ['status' => $response->status()]);
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return null;
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}
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}
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private function prompt(string $priceList): string
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{
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return <<<PROMPT
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You are analyzing Brent crude oil price data for a UK fuel price alert service.
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Predict the short-term direction over the next 3–5 days.
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$data = json_decode($response->json('choices.0.message.content') ?? '{}', true);
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Recent Brent crude prices (USD/barrel):
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{$priceList}
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if (! isset($data['direction'], $data['confidence'], $data['reasoning'])) {
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Log::error(self::class.': unexpected response format', ['data' => $data]);
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Respond with direction (rising, falling, or flat), a confidence score (0–85),
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and a one-sentence reasoning.
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PROMPT;
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return null;
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}
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return $data;
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}
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}
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