Protokoll #3217

ID3217
Zeitstempel2025-12-22 02:07:12.953902
Clientroot
IP145.224.96.190
Modellclaude-sonnet-4-20250514
Statuscompleted
Tokens810 (Input: 48, Output: 762)
Dauer90 ms
Request-Zeit2025-12-22 02:07:12.953902
Response-Zeit2025-12-22 02:07:13.043533

Request

{
    "event": "PreToolUse",
    "tool_name": "Read",
    "tool_input": {
        "file_path": "\/var\/www\/dev.campus.systemische-tools.de\/src\/Controller\/SemanticExplorerController.php",
        "offset": 170,
        "limit": 100
    }
}

Response

{
    "tool_response": {
        "type": "text",
        "file": {
            "filePath": "\/var\/www\/dev.campus.systemische-tools.de\/src\/Controller\/SemanticExplorerController.php",
            "content": "        ]);\n    }\n\n    \/**\n     * Vektor-Suche in documents Collection\n     *\/\n    private function vectorSearch(string $query, int $limit): array\n    {\n        \/\/ Embedding generieren\n        $embedding = $this->getEmbedding($query);\n        if (empty($embedding)) {\n            return [];\n        }\n\n        \/\/ Qdrant suchen\n        $response = $this->qdrantSearch($embedding, $limit);\n        if (empty($response)) {\n            return [];\n        }\n\n        \/\/ Chunk-Details aus DB laden\n        $results = [];\n        foreach ($response as $point) {\n            $chunkId = $point['payload']['chunk_id'] ?? null;\n            if ($chunkId === null) {\n                continue;\n            }\n\n            $chunk = $this->repository->getChunkById($chunkId);\n\n            if ($chunk !== null) {\n                $chunk['score'] = $point['score'];\n                $chunk['heading_path_decoded'] = json_decode($chunk['heading_path'] ?? '[]', true) ?: [];\n                $results[] = $chunk;\n            }\n        }\n\n        return $results;\n    }\n\n    \/**\n     * Embedding via Ollama\n     *\/\n    private function getEmbedding(string $text): array\n    {\n        $ch = curl_init('http:\/\/localhost:11434\/api\/embeddings');\n        curl_setopt_array($ch, [\n            CURLOPT_RETURNTRANSFER => true,\n            CURLOPT_POST => true,\n            CURLOPT_HTTPHEADER => ['Content-Type: application\/json'],\n            CURLOPT_POSTFIELDS => json_encode([\n                'model' => 'mxbai-embed-large',\n                'prompt' => $text,\n            ]),\n        ]);\n\n        $response = curl_exec($ch);\n        curl_close($ch);\n\n        $data = json_decode($response, true);\n\n        return $data['embedding'] ?? [];\n    }\n\n    \/**\n     * Qdrant-Suche\n     *\/\n    private function qdrantSearch(array $embedding, int $limit): array\n    {\n        $ch = curl_init('http:\/\/localhost:6333\/collections\/documents\/points\/search');\n        curl_setopt_array($ch, [\n            CURLOPT_RETURNTRANSFER => true,\n            CURLOPT_POST => true,\n            CURLOPT_HTTPHEADER => ['Content-Type: application\/json'],\n            CURLOPT_POSTFIELDS => json_encode([\n                'vector' => $embedding,\n                'limit' => $limit,\n                'with_payload' => true,\n            ]),\n        ]);\n\n        $response = curl_exec($ch);\n        curl_close($ch);\n\n        $data = json_decode($response, true);\n\n        return $data['result'] ?? [];\n    }\n\n    \/**\n     * GET \/semantic-explorer\/semantik\n     * Semantische Analyse pro Chunk\n     *\/\n    public function semantik(): void\n    {\n        $sentiment = $_GET['sentiment'] ?? '';\n        $page = max(1, (int) ($_GET['page'] ?? 1));\n        $limit = 50;\n        $offset = ($page - 1) * $limit;\n",
            "numLines": 100,
            "startLine": 170,
            "totalLines": 292
        }
    }
}
← Vorheriger Zur Liste Nächster →