<?php

namespace App\Services;

use Illuminate\Support\Facades\Http;
use Throwable;

class AiChatService
{
    public function __construct(
        private readonly OllamaService $ollama
    ) {
    }

    public function isAvailable(): bool
    {
        return $this->ollama->isConfigured();
    }

    /**
     * @param  array<int, array{role: string, content: string}>  $history
     * @return array{answer: string, chunks: array<int, array<string, mixed>>, meta: array<string, mixed>}
     */
    public function chat(
        string $query,
        string $username,
        string $displayName,
        string $jobTitle = '',
        array $history = [],
        int $contextLimit = 5
    ): array {
        $chunks = $this->retrieveContext($query, $contextLimit);
        $answer = $this->generate($query, $username, $displayName, $jobTitle, $chunks, $history);

        return [
            'answer' => $answer,
            'chunks' => $chunks,
            'meta' => [
                'query' => $query,
                'context_count' => count($chunks),
                'model' => config('ollama.chat_model'),
            ],
        ];
    }

    /**
     * Embed query → similarity search di pgvector code_chunks.
     *
     * @return array<int, array<string, mixed>>
     */
    private function retrieveContext(string $query, int $limit): array
    {
        $baseUrl = rtrim((string) config('ollama.base_url'), '/');
        $embedModel = (string) config('ollama.embed_model', 'nomic-embed-text');

        try {
            $resp = Http::timeout(30)
                ->post($baseUrl.'/api/embeddings', [
                    'model' => $embedModel,
                    'prompt' => $query,
                ]);

            if (! $resp->successful()) {
                return [];
            }

            $embedding = $resp->json('embedding');
            if (! is_array($embedding) || count($embedding) !== 768) {
                return [];
            }

            $pgHost = (string) config('pgvector.host', '10.100.1.24');
            $pgPort = (int) config('pgvector.port', 5433);
            $pgDb   = (string) config('pgvector.database', 'geonet_project_search');
            $pgUser = (string) config('pgvector.username', 'geonet_ai');
            $pgPass = (string) config('pgvector.password', '');

            $dsn = "pgsql:host={$pgHost};port={$pgPort};dbname={$pgDb}";
            $pdo = new \PDO($dsn, $pgUser, $pgPass, [\PDO::ATTR_ERRMODE => \PDO::ERRMODE_EXCEPTION]);

            $vectorStr = '['.implode(',', $embedding).']';
            $sql = "
                SELECT file_path, start_line, end_line, language, repo,
                       content,
                       1 - (embedding <=> :vec::vector) AS similarity
                FROM code_chunks
                ORDER BY embedding <=> :vec2::vector
                LIMIT :limit
            ";

            $stmt = $pdo->prepare($sql);
            $stmt->execute([':vec' => $vectorStr, ':vec2' => $vectorStr, ':limit' => $limit]);

            return array_map(fn ($row) => [
                'repo'       => $row['repo'],
                'file_path'  => $row['file_path'],
                'start_line' => (int) $row['start_line'],
                'end_line'   => (int) $row['end_line'],
                'language'   => $row['language'],
                'content'    => $row['content'],
                'similarity' => round((float) $row['similarity'], 4),
            ], $stmt->fetchAll(\PDO::FETCH_ASSOC));

        } catch (Throwable) {
            return [];
        }
    }

    /**
     * @param  array<int, array<string, mixed>>  $chunks
     * @param  array<int, array{role: string, content: string}>  $history
     */
    private function generate(
        string $query,
        string $username,
        string $displayName,
        string $jobTitle,
        array $chunks,
        array $history
    ): string {
        $contextBlock = '';
        if ($chunks !== []) {
            $contextBlock = "\n\n### Konteks dari Codebase:\n";
            foreach ($chunks as $i => $chunk) {
                $contextBlock .= sprintf(
                    "\n[%d] %s:%d-%d\n```%s\n%s\n```\n",
                    $i + 1,
                    $chunk['file_path'],
                    $chunk['start_line'],
                    $chunk['end_line'],
                    $chunk['language'] ?? '',
                    trim($chunk['content'])
                );
            }
        }

        $identity = "Nama: {$displayName}";
        if ($jobTitle !== '') {
            $identity .= ", Jabatan: {$jobTitle}";
        }

        $system = <<<SYS
Anda adalah AI assistant on-premise untuk tim IT GIS Portal (Geonet).
Jawab dalam Bahasa Indonesia yang formal dan ringkas.
User yang sedang chat: {$identity} (username: {$username}).
Gunakan konteks codebase yang disediakan bila relevan.
Jangan mengarang path file atau nama fungsi yang tidak ada di konteks.
Bila konteks tidak relevan, jawab berdasarkan pengetahuan umum.
SYS;

        $messages = [['role' => 'system', 'content' => $system]];

        foreach (array_slice($history, -10) as $item) {
            $role = $item['role'] ?? '';
            $content = $item['content'] ?? '';
            if (! in_array($role, ['user', 'assistant'], true) || $content === '') {
                continue;
            }
            $messages[] = ['role' => $role, 'content' => $content];
        }

        $userContent = $query.$contextBlock;
        $messages[] = ['role' => 'user', 'content' => $userContent];

        try {
            return $this->ollama->chat($messages);
        } catch (Throwable $e) {
            return 'Maaf, AI sedang tidak tersedia: '.$e->getMessage();
        }
    }
}