<?php
/**
 * Gemini Service Provider.
 *
 * @package AISupportAssistant\Providers
 */

namespace AISupportAssistant\Providers;

use AISupportAssistant\Admin\Settings;
use AISupportAssistant\Helpers\Logger;
use AISupportAssistant\Helpers\ConnectorHelper;

if ( ! defined( 'ABSPATH' ) ) {
	exit;
}

/**
 * Class GeminiProvider
 */
class GeminiProvider implements EmbeddingProviderInterface, ChatProviderInterface {

	/**
	 * Custom injected API key.
	 *
	 * @var string|null
	 */
	private ?string $custom_api_key = null;

	/**
	 * Constructor.
	 *
	 * @param string|null $custom_api_key Optional custom API key.
	 */
	public function __construct( ?string $custom_api_key = null ) {
		$this->custom_api_key = $custom_api_key;
	}

	/**
	 * Retrieve settings instance.
	 *
	 * @return Settings
	 */
	private function get_settings(): Settings {
		return Settings::get_instance();
	}

	/**
	 * Fetch API Key.
	 *
	 * @return string
	 */
	private function get_api_key(): string {
		if ( ! empty( $this->custom_api_key ) ) {
			return $this->custom_api_key;
		}

		$settings = $this->get_settings();
		$direct_key = (string) $settings->get( 'gemini_api_key', '' );
		if ( ! empty( $direct_key ) ) {
			return $direct_key;
		}

		$connector_key = ConnectorHelper::get_connector_api_key( 'google' );
		if ( empty( $connector_key ) ) {
			$connector_key = ConnectorHelper::get_connector_api_key( 'gemini' );
		}

		return $connector_key;
	}

	/**
	 * Retrieve vector embedding representation of text using gemini-embedding-001.
	 *
	 * @param string $text Input text block.
	 * @return array Float vector array.
	 */
	public function get_embedding( string $text ): array {
		$api_key = $this->get_api_key();
		if ( empty( $api_key ) ) {
			Logger::error( 'Gemini API key is missing. Cannot generate embedding.' );
			throw new \Exception( esc_html__( 'Gemini API key is missing. Please save your API key in settings.', 'ai-support-assistant' ) );
		}

		$model = $this->get_settings()->get( 'gemini_embedding_model', 'gemini-embedding-001' );
		$valid_embed_models = array( 'gemini-embedding-001' );
		if ( ! in_array( $model, $valid_embed_models, true ) ) {
			$model = 'gemini-embedding-001';
		}

		// Gemini Embed API endpoint.
		// phpcs:ignore PluginCheck.CodeAnalysis.AIProvider.DirectIntegration -- Direct integration provided as optional fallback alongside WordPress Native AI Client.
		$url = 'https://generativelanguage.googleapis.com/v1beta/models/' . $model . ':embedContent?key=' . $api_key;
		
		$body = array(
			'model'   => 'models/' . $model,
			'content' => array(
				'parts' => array(
					array( 'text' => $text ),
				),
			),
		);

		Logger::debug( 'Generating Gemini embedding', array( 'model' => $model ) );

		$response = wp_safe_remote_post(
			$url,
			array(
				'headers' => array( 'Content-Type' => 'application/json' ),
				'body'    => wp_json_encode( $body ),
				'timeout' => 30,
			)
		);

		if ( is_wp_error( $response ) ) {
			$err_msg = $response->get_error_message();
			Logger::error( 'Gemini Embedding API error: ' . $err_msg );
			/* translators: %s: Gemini connection error message. */
			throw new \Exception( esc_html( sprintf( __( 'Gemini API connection error: %s', 'ai-support-assistant' ), $err_msg ) ) );
		}

		$code = wp_remote_retrieve_response_code( $response );
		$res_body = wp_remote_retrieve_body( $response );

		if ( 200 !== $code ) {
			Logger::error( "Gemini Embedding API error (HTTP $code)", array( 'response' => $res_body ) );
			$decoded = json_decode( $res_body, true );
			$err_msg = ! empty( $decoded['error']['message'] ) ? $decoded['error']['message'] : "HTTP $code";
			/* translators: %s: Gemini API error details. */
			throw new \Exception( esc_html( sprintf( __( 'Gemini API error: %s', 'ai-support-assistant' ), $err_msg ) ) );
		}

		$decoded = json_decode( $res_body, true );
		if ( ! empty( $decoded['embedding']['values'] ) ) {
			return $decoded['embedding']['values'];
		}

		Logger::error( 'Gemini Embedding response is malformed.', array( 'response' => $res_body ) );
		throw new \Exception( esc_html__( 'Gemini Embedding response is malformed.', 'ai-support-assistant' ) );
	}

	/**
	 * Generate chat response using Gemini models.
	 *
	 * @param array  $chunks   Array of relevant document chunks.
	 * @param string $question User query text.
	 * @param array  $history  Recent conversation history.
	 * @return string The generated assistant response.
	 */
	public function generate_response( array $chunks, string $question, array $history = array() ): string {
		$api_key = $this->get_api_key();
		if ( empty( $api_key ) ) {
			return __( "I couldn't process this query. Gemini API Key is missing.", 'ai-support-assistant' );
		}

		$settings = $this->get_settings();
		$model    = $settings->get( 'gemini_chat_model', 'gemini-3.1-flash-lite' );
		$valid_chat_models = array( 'gemini-3.1-flash-lite' );
		if ( ! in_array( $model, $valid_chat_models, true ) ) {
			$model = 'gemini-3.1-flash-lite';
		}
		$temp     = $settings->get( 'temperature', 0.2 );
		$max_t    = $settings->get( 'max_tokens', 1000 );

		// Format context documentation blocks.
		$context_str = '';
		foreach ( $chunks as $chunk ) {
			$page_info = ! empty( $chunk['page_number'] ) ? ' | Page: ' . $chunk['page_number'] : '';
			$context_str .= sprintf(
				"[Document: %s%s]\n%s\n---\n",
				$chunk['filename'] ?? 'Unknown',
				$page_info,
				$chunk['chunk_text']
			);
		}

		// Compile system instruction.
		$custom_instruction = $settings->get( 'ai_system_instruction', "You are a professional customer support assistant.\nAnswer using ONLY the supplied documentation.\nFormat your response cleanly using structured Markdown bullet points (* or -) and bold section titles so it is clean, elegant, and easy to read.\nIf the answer is not found, say:\n\"I couldn't find that information in the uploaded documentation.\"\nDo not invent information." );
		$system_prompt = $custom_instruction . "\n\nDocumentation:\n" . $context_str;

		$contents = array();

		// Hydrate dialogue history (if exists). Note: Gemini roles are 'user' and 'model'.
		if ( ! empty( $history ) ) {
			foreach ( $history as $turn ) {
				$contents[] = array(
					'role'  => 'user',
					'parts' => array(
						array( 'text' => $turn['question'] ),
					),
				);
				$contents[] = array(
					'role'  => 'model',
					'parts' => array(
						array( 'text' => $turn['answer'] ),
					),
				);
			}
		}

		// Append the actual query.
		$contents[] = array(
			'role'  => 'user',
			'parts' => array(
				array( 'text' => "Question: $question" ),
			),
		);

		// Gemini GenerateContent endpoint.
		// phpcs:ignore PluginCheck.CodeAnalysis.AIProvider.DirectIntegration -- Direct integration provided as optional fallback alongside WordPress Native AI Client.
		$url = 'https://generativelanguage.googleapis.com/v1beta/models/' . $model . ':generateContent?key=' . $api_key;
		
		$body = array(
			'contents'          => $contents,
			'systemInstruction' => array(
				'parts' => array(
					array( 'text' => $system_prompt ),
				),
			),
			'generationConfig'  => array(
				'temperature'     => $temp,
				'maxOutputTokens' => $max_t,
			),
		);

		Logger::debug( 'Requesting Gemini Chat response', array( 'model' => $model ) );

		$response = wp_safe_remote_post(
			$url,
			array(
				'headers' => array( 'Content-Type' => 'application/json' ),
				'body'    => wp_json_encode( $body ),
				'timeout' => 45,
			)
		);

		if ( is_wp_error( $response ) ) {
			Logger::error( 'Gemini Chat API error: ' . $response->get_error_message() );
			return __( 'Sorry, an error occurred with the AI service.', 'ai-support-assistant' );
		}

		$code = wp_remote_retrieve_response_code( $response );
		$res_body = wp_remote_retrieve_body( $response );

		if ( 200 !== $code ) {
			Logger::error( "Gemini Chat API error (HTTP $code)", array( 'response' => $res_body ) );
			$decoded = json_decode( $res_body, true );
			if ( ! empty( $decoded['error']['message'] ) ) {
				$msg = $decoded['error']['message'];
				if ( 429 === $code || false !== strpos( strtolower( $msg ), 'quota' ) ) {
					return __( 'Google Gemini API Quota Exceeded: Your Google API Key has exceeded its usage quota. Please generate a new API key or check your quota at https://ai.google.dev.', 'ai-support-assistant' );
				}
				/* translators: %s: Gemini API error message. */
				return sprintf( __( 'Google Gemini API Error: %s', 'ai-support-assistant' ), $msg );
			}
			return __( 'Sorry, the AI service returned an error.', 'ai-support-assistant' );
		}

		$decoded = json_decode( $res_body, true );
		if ( ! empty( $decoded['candidates'][0]['content']['parts'][0]['text'] ) ) {
			return trim( $decoded['candidates'][0]['content']['parts'][0]['text'] );
		}

		Logger::error( 'Gemini Chat Response is malformed.', array( 'response' => $res_body ) );
		return __( 'Sorry, a malformed response was received from the AI service.', 'ai-support-assistant' );
	}
}