Protokoll #3901

{
    "event": "PreToolUse",
    "tool_name": "Read",
    "tool_input": {
        "file_path": "\/var\/www\/dev.campus.systemische-tools.de\/src\/Infrastructure\/AI\/ChatService.php",
        "offset": 55,
        "limit": 25
    }
}

{
    "tool_response": {
        "type": "text",
        "file": {
            "filePath": "\/var\/www\/dev.campus.systemische-tools.de\/src\/Infrastructure\/AI\/ChatService.php",
            "content": "     *\n     * @param string        $question           The user's question to answer\n     * @param string        $model              The LLM model (claude-* or ollama:*)\n     * @param array<string> $collections        Qdrant collections to search (empty = no RAG)\n     * @param int           $limit              Maximum number of document chunks to retrieve (default: 5)\n     * @param string|null   $stylePrompt        Optional style prompt from author profile\n     * @param string|null   $customSystemPrompt Optional custom system prompt (replaces default if set)\n     * @param float         $temperature        Sampling temperature 0.0-1.0 (default: 0.7)\n     * @param int           $maxTokens          Maximum tokens in response (default: 4096)\n     *\n     * @return array{\n     *     question: string,\n     *     answer: string,\n     *     sources: array<int, array{title: string, score: float, content?: string}>,\n     *     model: string,\n     *     usage?: array{input_tokens: int, output_tokens: int},\n     *     chunks_used: int\n     * } Complete chat response with answer, sources, and metadata\n     *\n     * @throws RuntimeException If embedding generation fails\n     * @throws RuntimeException If vector search fails\n     * @throws RuntimeException If LLM request fails\n     *\n     * @example\n     * $chat = new ChatService($ollama, $qdrant, $claude);",
            "numLines": 25,
            "startLine": 55,
            "totalLines": 353
        }
    }
}