{
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"filePath": "\/var\/www\/dev.campus.systemische-tools.de\/src\/UseCases\/Docs\/DocumentationChatUseCase.php",
"content": "<?php\n\ndeclare(strict_types=1);\n\nnamespace UseCases\\Docs;\n\n\/\/ @responsibility: RAG-basierter Chat über Dokumentation\n\nuse Infrastructure\\AI\\OllamaService;\nuse Infrastructure\\Docs\\ChunkSyncService;\n\nclass DocumentationChatUseCase\n{\n public function __construct(\n private ChunkSyncService $syncService,\n private OllamaService $ollamaService\n ) {\n }\n\n \/**\n * Execute documentation chat.\n *\n * @param string $question User question\n * @param string $model LLM model to use\n * @param int $limit Number of context chunks\n * @return array{answer: string, sources: array<int, array{id: int, path: string, title: string, score: float}>}\n *\/\n public function execute(string $question, string $model = 'mistral', int $limit = 5): array\n {\n \/\/ Get relevant chunks via semantic search\n $chunks = $this->syncService->search($question, $limit);\n\n if (empty($chunks)) {\n return [\n 'answer' => 'Leider konnte ich keine relevanten Informationen in der Dokumentation finden.',\n 'sources' => [],\n ];\n }\n\n \/\/ Build context from chunks\n $context = $this->buildContext($chunks);\n\n \/\/ Generate answer using LLM\n $prompt = $this->buildPrompt($question, $context);\n $answer = $this->ollamaService->generate($prompt, $model, 0.3);\n\n \/\/ Map sources\n $sources = array_map(static fn (array $chunk): array => [\n 'id' => $chunk['doc_id'],\n 'path' => $chunk['path'],",
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