Protokoll #6499

{
    "event": "PreToolUse",
    "tool_name": "Write",
    "tool_input": {
        "file_path": "\/opt\/scripts\/pipeline\/protokoll.py",
        "content": "\"\"\"\nKI-Protokoll Integration for Pipeline\nLogs all LLM calls to ki_dev.protokoll for tracking and cost analysis.\n\"\"\"\n\nimport time\nfrom datetime import datetime\n\nimport mysql.connector\n\nfrom config import DB_PROTOKOLL_CONFIG\n\n\nclass Protokoll:\n    \"\"\"Logger for LLM calls to ki_dev.protokoll.\"\"\"\n\n    def __init__(self, client_name=\"pipeline\"):\n        self.client_name = client_name\n        self.conn = None\n\n    def connect(self):\n        \"\"\"Connect to protokoll database.\"\"\"\n        if not self.conn or not self.conn.is_connected():\n            self.conn = mysql.connector.connect(**DB_PROTOKOLL_CONFIG)\n\n    def disconnect(self):\n        \"\"\"Disconnect from database.\"\"\"\n        if self.conn and self.conn.is_connected():\n            self.conn.close()\n            self.conn = None\n\n    def log_llm_call(\n        self,\n        request: str,\n        response: str = None,\n        model_name: str = None,\n        tokens_input: int = 0,\n        tokens_output: int = 0,\n        duration_ms: int = 0,\n        status: str = \"completed\",\n        error_message: str = None,\n    ):\n        \"\"\"\n        Log an LLM call to ki_dev.protokoll.\n\n        Args:\n            request: The prompt\/request sent to the LLM\n            response: The LLM response (truncated if too long)\n            model_name: Name of the model used\n            tokens_input: Input token count\n            tokens_output: Output token count\n            duration_ms: Duration in milliseconds\n            status: 'pending', 'completed', or 'error'\n            error_message: Error message if status is 'error'\n        \"\"\"\n        self.connect()\n\n        try:\n            cursor = self.conn.cursor()\n            now = datetime.now()\n\n            # Truncate response if too long (TEXT limit ~65KB)\n            if response and len(response) > 60000:\n                response = response[:60000] + \"...[truncated]\"\n\n            cursor.execute(\n                \"\"\"INSERT INTO protokoll\n                   (request_ip, client_name, request, request_timestamp,\n                    response, response_timestamp, duration_ms,\n                    tokens_input, tokens_output, tokens_total,\n                    model_name, status, error_message)\n                   VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)\"\"\",\n                (\n                    \"127.0.0.1\",  # Pipeline runs locally\n                    self.client_name,\n                    request[:10000] if request else \"\",  # Truncate request too\n                    now,\n                    response,\n                    now if response else None,\n                    duration_ms,\n                    tokens_input,\n                    tokens_output,\n                    tokens_input + tokens_output,\n                    model_name,\n                    status,\n                    error_message,\n                ),\n            )\n            self.conn.commit()\n            cursor.close()\n            return cursor.lastrowid\n\n        except Exception as e:\n            print(f\"Protokoll logging failed: {e}\")\n            return None\n\n\nclass LLMCallContext:\n    \"\"\"Context manager for timing and logging LLM calls.\"\"\"\n\n    def __init__(self, protokoll: Protokoll, request: str, model_name: str):\n        self.protokoll = protokoll\n        self.request = request\n        self.model_name = model_name\n        self.start_time = None\n        self.response = None\n        self.tokens_input = 0\n        self.tokens_output = 0\n        self.error = None\n\n    def __enter__(self):\n        self.start_time = time.time()\n        return self\n\n    def __exit__(self, exc_type, exc_val, exc_tb):\n        duration_ms = int((time.time() - self.start_time) * 1000)\n\n        if exc_type is not None:\n            self.protokoll.log_llm_call(\n                request=self.request,\n                response=None,\n                model_name=self.model_name,\n                duration_ms=duration_ms,\n                status=\"error\",\n                error_message=str(exc_val),\n            )\n        else:\n            self.protokoll.log_llm_call(\n                request=self.request,\n                response=self.response,\n                model_name=self.model_name,\n                tokens_input=self.tokens_input,\n                tokens_output=self.tokens_output,\n                duration_ms=duration_ms,\n                status=\"completed\",\n            )\n\n        return False  # Don't suppress exceptions\n\n    def set_response(self, response: str, tokens_input: int = 0, tokens_output: int = 0):\n        \"\"\"Set response data for logging.\"\"\"\n        self.response = response\n        self.tokens_input = tokens_input\n        self.tokens_output = tokens_output\n\n\n# Global instance for pipeline\nprotokoll = Protokoll(\"pipeline\")\n"
    }
}

{
    "tool_response": {
        "type": "create",
        "filePath": "\/opt\/scripts\/pipeline\/protokoll.py",
        "content": "\"\"\"\nKI-Protokoll Integration for Pipeline\nLogs all LLM calls to ki_dev.protokoll for tracking and cost analysis.\n\"\"\"\n\nimport time\nfrom datetime import datetime\n\nimport mysql.connector\n\nfrom config import DB_PROTOKOLL_CONFIG\n\n\nclass Protokoll:\n    \"\"\"Logger for LLM calls to ki_dev.protokoll.\"\"\"\n\n    def __init__(self, client_name=\"pipeline\"):\n        self.client_name = client_name\n        self.conn = None\n\n    def connect(self):\n        \"\"\"Connect to protokoll database.\"\"\"\n        if not self.conn or not self.conn.is_connected():\n            self.conn = mysql.connector.connect(**DB_PROTOKOLL_CONFIG)\n\n    def disconnect(self):\n        \"\"\"Disconnect from database.\"\"\"\n        if self.conn and self.conn.is_connected():\n            self.conn.close()\n            self.conn = None\n\n    def log_llm_call(\n        self,\n        request: str,\n        response: str = None,\n        model_name: str = None,\n        tokens_input: int = 0,\n        tokens_output: int = 0,\n        duration_ms: int = 0,\n        status: str = \"completed\",\n        error_message: str = None,\n    ):\n        \"\"\"\n        Log an LLM call to ki_dev.protokoll.\n\n        Args:\n            request: The prompt\/request sent to the LLM\n            response: The LLM response (truncated if too long)\n            model_name: Name of the model used\n            tokens_input: Input token count\n            tokens_output: Output token count\n            duration_ms: Duration in milliseconds\n            status: 'pending', 'completed', or 'error'\n            error_message: Error message if status is 'error'\n        \"\"\"\n        self.connect()\n\n        try:\n            cursor = self.conn.cursor()\n            now = datetime.now()\n\n            # Truncate response if too long (TEXT limit ~65KB)\n            if response and len(response) > 60000:\n                response = response[:60000] + \"...[truncated]\"\n\n            cursor.execute(\n                \"\"\"INSERT INTO protokoll\n                   (request_ip, client_name, request, request_timestamp,\n                    response, response_timestamp, duration_ms,\n                    tokens_input, tokens_output, tokens_total,\n                    model_name, status, error_message)\n                   VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)\"\"\",\n                (\n                    \"127.0.0.1\",  # Pipeline runs locally\n                    self.client_name,\n                    request[:10000] if request else \"\",  # Truncate request too\n                    now,\n                    response,\n                    now if response else None,\n                    duration_ms,\n                    tokens_input,\n                    tokens_output,\n                    tokens_input + tokens_output,\n                    model_name,\n                    status,\n                    error_message,\n                ),\n            )\n            self.conn.commit()\n            cursor.close()\n            return cursor.lastrowid\n\n        except Exception as e:\n            print(f\"Protokoll logging failed: {e}\")\n            return None\n\n\nclass LLMCallContext:\n    \"\"\"Context manager for timing and logging LLM calls.\"\"\"\n\n    def __init__(self, protokoll: Protokoll, request: str, model_name: str):\n        self.protokoll = protokoll\n        self.request = request\n        self.model_name = model_name\n        self.start_time = None\n        self.response = None\n        self.tokens_input = 0\n        self.tokens_output = 0\n        self.error = None\n\n    def __enter__(self):\n        self.start_time = time.time()\n        return self\n\n    def __exit__(self, exc_type, exc_val, exc_tb):\n        duration_ms = int((time.time() - self.start_time) * 1000)\n\n        if exc_type is not None:\n            self.protokoll.log_llm_call(\n                request=self.request,\n                response=None,\n                model_name=self.model_name,\n                duration_ms=duration_ms,\n                status=\"error\",\n                error_message=str(exc_val),\n            )\n        else:\n            self.protokoll.log_llm_call(\n                request=self.request,\n                response=self.response,\n                model_name=self.model_name,\n                tokens_input=self.tokens_input,\n                tokens_output=self.tokens_output,\n                duration_ms=duration_ms,\n                status=\"completed\",\n            )\n\n        return False  # Don't suppress exceptions\n\n    def set_response(self, response: str, tokens_input: int = 0, tokens_output: int = 0):\n        \"\"\"Set response data for logging.\"\"\"\n        self.response = response\n        self.tokens_input = tokens_input\n        self.tokens_output = tokens_output\n\n\n# Global instance for pipeline\nprotokoll = Protokoll(\"pipeline\")\n",
        "structuredPatch": [],
        "originalFile": null
    }
}