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169 lines
6.8 KiB
169 lines
6.8 KiB
<?php
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declare(strict_types=1);
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namespace flight\commands;
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use Ahc\Cli\Input\Command;
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/**
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* @property-read ?string $credsFile
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* @property-read ?string $baseDir
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*/
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class AiGenerateInstructionsCommand extends Command
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{
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/**
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* Constructor for the AiGenerateInstructionsCommand class.
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*
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* Initializes a new instance of the command.
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*/
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public function __construct()
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{
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parent::__construct('ai:generate-instructions', 'Generate project-specific AI coding instructions');
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$this->option('--creds-file', 'Path to .runway-creds.json file', null, '');
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$this->option('--base-dir', 'Project base directory (for testing or custom use)', null, '');
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}
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/**
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* Executes the command logic for generating AI instructions.
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*
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* This method is called to perform the main functionality of the
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* AiGenerateInstructionsCommand. It should contain the steps required
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* to generate and output instructions using AI, based on the command's
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* configuration and input.
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*
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* @return int
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*/
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public function execute()
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{
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$io = $this->app()->io();
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$baseDir = $this->baseDir ? rtrim($this->baseDir, DIRECTORY_SEPARATOR) . DIRECTORY_SEPARATOR : getcwd() . DIRECTORY_SEPARATOR;
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$runwayCredsFile = $this->credsFile ?: $baseDir . '.runway-creds.json';
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// Check for runway creds
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if (!file_exists($runwayCredsFile)) {
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$io->error('Missing .runway-creds.json. Please run the \'ai:init\' command first.', true);
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return 1;
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}
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$io->info('Let\'s gather some project details to generate AI coding instructions.', true);
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// Ask questions
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$projectDesc = $io->prompt('Please describe what your project is for?');
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$database = $io->prompt('What database are you planning on using? (e.g. MySQL, SQLite, PostgreSQL, none)', 'none');
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$templating = $io->prompt('What HTML templating engine will you plan on using (if any)? (recommend latte)', 'latte');
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$security = $io->confirm('Is security an important element of this project?', 'y');
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$performance = $io->confirm('Is performance and speed an important part of this project?', 'y');
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$composerLibs = $io->prompt('What major composer libraries will you be using if you know them right now?', 'none');
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$envSetup = $io->prompt('How will you set up your development environment? (e.g. Docker, Vagrant, PHP dev server, other)', 'Docker');
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$teamSize = $io->prompt('How many developers will be working on this project?', '1');
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$api = $io->confirm('Will this project expose an API?', 'n');
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$other = $io->prompt('Any other important requirements or context? (optional)', 'no');
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// Prepare prompt for LLM
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$contextFile = $baseDir . '.github/copilot-instructions.md';
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$context = file_exists($contextFile) ? file_get_contents($contextFile) : '';
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$userDetails = [
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'Project Description' => $projectDesc,
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'Database' => $database,
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'Templating Engine' => $templating,
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'Security Important' => $security ? 'yes' : 'no',
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'Performance Important' => $performance ? 'yes' : 'no',
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'Composer Libraries' => $composerLibs,
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'Environment Setup' => $envSetup,
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'Team Size' => $teamSize,
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'API' => $api ? 'yes' : 'no',
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'Other' => $other,
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];
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$detailsText = "";
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foreach ($userDetails as $k => $v) {
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$detailsText .= "$k: $v\n";
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}
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$prompt = <<<EOT
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You are an AI coding assistant. Update the following project instructions for this FlightPHP project based on the latest user answers. Only output the new instructions, no extra commentary.
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User answers:
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$detailsText
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Current instructions:
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$context
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EOT;
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// Read LLM creds
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$creds = json_decode(file_get_contents($runwayCredsFile), true);
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$apiKey = $creds['api_key'] ?? '';
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$model = $creds['model'] ?? 'gpt-4o';
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$baseUrl = $creds['base_url'] ?? 'https://api.openai.com';
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// Prepare curl call (OpenAI compatible)
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$headers = [
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'Content-Type: application/json',
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'Authorization: Bearer ' . $apiKey,
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];
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$data = [
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'model' => $model,
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'messages' => [
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['role' => 'system', 'content' => 'You are a helpful AI coding assistant focused on the Flight Framework for PHP. You are up to date with all your knowledge from https://docs.flightphp.com. As an expert into the programming language PHP, you are top notch at architecting out proper instructions for FlightPHP projects.'],
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['role' => 'user', 'content' => $prompt],
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],
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'temperature' => 0.2,
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];
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$jsonData = json_encode($data);
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// add info line that this may take a few minutes
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$io->info('Generating AI instructions, this may take a few minutes...', true);
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$result = $this->callLlmApi($baseUrl, $headers, $jsonData, $io);
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if ($result === false) {
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return 1;
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}
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$response = json_decode($result, true);
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$instructions = $response['choices'][0]['message']['content'] ?? '';
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if (!$instructions) {
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$io->error('No instructions returned from LLM.', true);
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return 1;
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}
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// Write to files
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$io->info('Updating .github/copilot-instructions.md, .cursor/rules/project-overview.mdc, and .windsurfrules...', true);
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if (!is_dir($baseDir . '.github')) {
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mkdir($baseDir . '.github', 0755, true);
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}
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if (!is_dir($baseDir . '.cursor/rules')) {
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mkdir($baseDir . '.cursor/rules', 0755, true);
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}
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file_put_contents($baseDir . '.github/copilot-instructions.md', $instructions);
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file_put_contents($baseDir . '.cursor/rules/project-overview.mdc', $instructions);
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file_put_contents($baseDir . '.windsurfrules', $instructions);
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$io->ok('AI instructions updated successfully.', true);
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return 0;
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}
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/**
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* Make the LLM API call using curl
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*
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* @param string $baseUrl
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* @param array<int,string> $headers
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* @param string $jsonData
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* @param object $io
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*
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* @return string|false
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*
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* @codeCoverageIgnore
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*/
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protected function callLlmApi($baseUrl, $headers, $jsonData, $io)
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{
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$ch = curl_init($baseUrl . '/v1/chat/completions');
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curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
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curl_setopt($ch, CURLOPT_POST, true);
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curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
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curl_setopt($ch, CURLOPT_POSTFIELDS, $jsonData);
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$result = curl_exec($ch);
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if (curl_errno($ch)) {
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$io->error('Failed to call LLM API: ' . curl_error($ch), true);
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curl_close($ch);
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return false;
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}
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curl_close($ch);
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return $result;
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}
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}
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