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| import json | |
| import random | |
| from typing import Any, Dict, List, Optional | |
| import numpy as np | |
| def set_seed(seed: int) -> None: | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| def format_conversation(history: List[Dict], last_n: int = 5) -> str: | |
| lines = [] | |
| for msg in history[-last_n:]: | |
| role = msg.get("role", "unknown").upper() | |
| content = msg.get("content", msg.get("message", "")) | |
| action = msg.get("action", "") | |
| if action: | |
| lines.append(f"[{role}] ({action}) {content}") | |
| else: | |
| lines.append(f"[{role}] {content}") | |
| return "\n".join(lines) | |
| def validate_json(data: Any, schema: Dict) -> bool: | |
| if not isinstance(data, dict): | |
| return False | |
| for key, expected_type in schema.items(): | |
| if key not in data: | |
| return False | |
| if expected_type is not None and not isinstance(data[key], expected_type): | |
| return False | |
| return True | |
| POLICY_SCHEMA = { | |
| "version": str, | |
| "policies": dict, | |
| } | |
| def validate_policy_file(data: Dict) -> bool: | |
| return validate_json(data, POLICY_SCHEMA) | |
| def deep_merge(base: Dict, overlay: Dict) -> Dict: | |
| result = base.copy() | |
| for key, value in overlay.items(): | |
| if key in result and isinstance(result[key], dict) and isinstance(value, dict): | |
| result[key] = deep_merge(result[key], value) | |
| else: | |
| result[key] = value | |
| return result | |