Implement Lakera Guard for AI Security

Integrate Lakera Guard into your Google ADK agent's input processing pipeline. Before any inference request is routed to DeepSeek R1 or the simulated Trainium, the Lakera API should scan the prompt for potential security threats like prompt injection, hate speech, or PII. If a threat is detected, the agent should block the request and log the incident. Provide the Python code for Lakera integration. ```python
import requests LAKERA_API_URL = "https://api.lakera.ai/v1/prompt_moderation"
LAKERA_API_KEY = "YOUR_LAKERA_API_KEY" def scan_prompt_with_lakera(prompt: str) -> dict: headers = {"Authorization": f"Bearer {LAKERA_API_KEY}"} payload = {"input": prompt} try: response = requests.post(LAKERA_API_URL, headers=headers, json=payload) response.raise_for_status() return response.json() except requests.exceptions.RequestException as e: print(f"Lakera API error: {e}") return {"flagged": False, "reason": "API_ERROR"} def secure_inference_router(prompt: str, user_id: str) -> str: scan_result = scan_prompt_with_lakera(prompt) if scan_result.get('flagged'): print(f"Prompt blocked by Lakera: {scan_result.get('reason')}") return "Your request was blocked due to security concerns." # If not flagged, proceed with existing routing logic # return agent_with_memory(prompt, user_id) # Call your routing agent return "Prompt allowed. Proceeding to inference."
```