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"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'],\n 'title' => $chunk['title'],\n 'score' => round($chunk['score'], 3),\n ], $chunks);\n\n return [\n 'answer' => $answer,\n 'sources' => $sources,\n ];\n }\n\n \/**\n * Build context from chunks.\n *\/\n private function buildContext(array $chunks): string\n {\n $parts = [];\n\n foreach ($chunks as $chunk) {\n $part = \"## {$chunk['title']}\\n\";\n $part .= \"Pfad: {$chunk['path']}\\n\";\n $part .= $chunk['content'];\n $parts[] = $part;\n }\n\n return implode(\"\\n\\n---\\n\\n\", $parts);\n }\n\n \/**\n * Build chat prompt.\n *\/\n private function buildPrompt(string $question, string $context): string\n {\n return <<<PROMPT\n Du bist ein Dokumentations-Assistent. Beantworte die Frage basierend auf dem bereitgestellten Kontext.\n\n KONTEXT:\n {$context}\n\n FRAGE:\n {$question}\n\n ANLEITUNG:\n - Antworte auf Deutsch\n - Sei präzise und hilfreich\n - Wenn der Kontext die Frage nicht beantwortet, sage das ehrlich\n - Verweise auf die relevanten Abschnitte der Dokumentation\n PROMPT;\n }\n}\n",
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