|
| 1 | +""" |
| 2 | +SQL Agent Training with Agent-Lightning |
| 3 | +======================================== |
| 4 | +
|
| 5 | +Demonstrates training a SQL agent with RL while enforcing |
| 6 | +safety policies through Agent OS. |
| 7 | +
|
| 8 | +The agent learns to: |
| 9 | +1. Generate accurate SQL queries |
| 10 | +2. NEVER violate safety policies (no DROP, DELETE, etc.) |
| 11 | +3. Stay within cost limits |
| 12 | +
|
| 13 | +Run: |
| 14 | + pip install agent-os-kernel agentlightning |
| 15 | + python sql_agent.py |
| 16 | +""" |
| 17 | + |
| 18 | +import asyncio |
| 19 | +import logging |
| 20 | +from typing import Optional |
| 21 | + |
| 22 | +# Configure logging |
| 23 | +logging.basicConfig(level=logging.INFO) |
| 24 | +logger = logging.getLogger(__name__) |
| 25 | + |
| 26 | +# ============================================================ |
| 27 | +# MOCK COMPONENTS (Replace with real implementations) |
| 28 | +# ============================================================ |
| 29 | + |
| 30 | +class MockKernelSpace: |
| 31 | + """Mock kernel for demonstration.""" |
| 32 | + |
| 33 | + def __init__(self, policy=None): |
| 34 | + self.policy = policy or [] |
| 35 | + self.violations = [] |
| 36 | + self._violation_callbacks = [] |
| 37 | + |
| 38 | + def on_policy_violation(self, callback): |
| 39 | + self._violation_callbacks.append(callback) |
| 40 | + |
| 41 | + def execute(self, agent, task): |
| 42 | + """Execute with policy checking.""" |
| 43 | + # Simulate policy check |
| 44 | + if "DROP" in str(task).upper() or "DELETE" in str(task).upper(): |
| 45 | + for cb in self._violation_callbacks: |
| 46 | + cb( |
| 47 | + policy_name="SQLPolicy", |
| 48 | + description="Dangerous SQL operation blocked", |
| 49 | + severity="critical", |
| 50 | + blocked=True, |
| 51 | + ) |
| 52 | + return None |
| 53 | + |
| 54 | + return {"result": f"Executed: {task}", "accuracy": 0.85} |
| 55 | + |
| 56 | + def reset(self): |
| 57 | + self.violations = [] |
| 58 | + |
| 59 | + |
| 60 | +class MockSQLPolicy: |
| 61 | + """Mock SQL policy.""" |
| 62 | + |
| 63 | + def __init__(self, allow=None, deny=None): |
| 64 | + self.allow = allow or ["SELECT"] |
| 65 | + self.deny = deny or ["DROP", "DELETE"] |
| 66 | + self.name = "SQLPolicy" |
| 67 | + |
| 68 | + |
| 69 | +class MockCostControlPolicy: |
| 70 | + """Mock cost control policy.""" |
| 71 | + |
| 72 | + def __init__(self, max_cost_usd=100): |
| 73 | + self.max_cost_usd = max_cost_usd |
| 74 | + self.name = "CostControlPolicy" |
| 75 | + |
| 76 | + |
| 77 | +# ============================================================ |
| 78 | +# TRAINING EXAMPLE |
| 79 | +# ============================================================ |
| 80 | + |
| 81 | +async def train_sql_agent(): |
| 82 | + """Train a SQL agent with governance.""" |
| 83 | + |
| 84 | + # Import Agent OS integration |
| 85 | + from agent_os.integrations.agent_lightning import ( |
| 86 | + GovernedRunner, |
| 87 | + PolicyReward, |
| 88 | + GovernedEnvironment, |
| 89 | + ) |
| 90 | + |
| 91 | + print("=" * 60) |
| 92 | + print("SQL Agent Training with Agent-Lightning + Agent OS") |
| 93 | + print("=" * 60) |
| 94 | + |
| 95 | + # 1. Create kernel with policies |
| 96 | + kernel = MockKernelSpace(policy=[ |
| 97 | + MockSQLPolicy( |
| 98 | + allow=["SELECT", "INSERT", "UPDATE"], |
| 99 | + deny=["DROP", "DELETE", "TRUNCATE"], |
| 100 | + ), |
| 101 | + MockCostControlPolicy(max_cost_usd=100), |
| 102 | + ]) |
| 103 | + |
| 104 | + print("\n✓ Kernel initialized with policies:") |
| 105 | + print(" - SQLPolicy: Allow SELECT/INSERT/UPDATE, Deny DROP/DELETE") |
| 106 | + print(" - CostControlPolicy: Max $100 per query") |
| 107 | + |
| 108 | + # 2. Create governed runner |
| 109 | + runner = GovernedRunner( |
| 110 | + kernel, |
| 111 | + fail_on_violation=False, |
| 112 | + log_violations=True, |
| 113 | + ) |
| 114 | + |
| 115 | + # Mock agent initialization |
| 116 | + class MockAgent: |
| 117 | + name = "SQLAgent" |
| 118 | + def __call__(self, task): |
| 119 | + return {"result": task, "accuracy": 0.9} |
| 120 | + |
| 121 | + runner.init(MockAgent()) |
| 122 | + runner.init_worker(0, None) |
| 123 | + |
| 124 | + print("\n✓ GovernedRunner initialized") |
| 125 | + |
| 126 | + # 3. Create policy-aware reward function |
| 127 | + def accuracy_reward(rollout): |
| 128 | + if rollout.success and rollout.task_output: |
| 129 | + return rollout.task_output.get("accuracy", 0.0) |
| 130 | + return 0.0 |
| 131 | + |
| 132 | + reward_fn = PolicyReward(kernel, base_reward_fn=accuracy_reward) |
| 133 | + print("✓ PolicyReward function created") |
| 134 | + |
| 135 | + # 4. Simulate training episodes |
| 136 | + print("\n" + "=" * 60) |
| 137 | + print("Training Episodes") |
| 138 | + print("=" * 60) |
| 139 | + |
| 140 | + test_queries = [ |
| 141 | + "SELECT * FROM users WHERE id = 1", |
| 142 | + "INSERT INTO logs (msg) VALUES ('hello')", |
| 143 | + "DROP TABLE users", # Should be blocked! |
| 144 | + "UPDATE users SET name = 'John' WHERE id = 1", |
| 145 | + "DELETE FROM users WHERE id = 1", # Should be blocked! |
| 146 | + "SELECT COUNT(*) FROM orders", |
| 147 | + ] |
| 148 | + |
| 149 | + total_reward = 0.0 |
| 150 | + violations_count = 0 |
| 151 | + |
| 152 | + for i, query in enumerate(test_queries): |
| 153 | + print(f"\nEpisode {i+1}: {query[:50]}...") |
| 154 | + |
| 155 | + # Execute through governed runner |
| 156 | + rollout = await runner.step(query) |
| 157 | + |
| 158 | + # Calculate reward |
| 159 | + reward = reward_fn(rollout, emit=False) |
| 160 | + total_reward += reward |
| 161 | + violations_count += len(rollout.violations) |
| 162 | + |
| 163 | + # Report |
| 164 | + status = "✅ SUCCESS" if rollout.success else "❌ BLOCKED" |
| 165 | + print(f" Status: {status}") |
| 166 | + print(f" Violations: {len(rollout.violations)}") |
| 167 | + print(f" Reward: {reward:.2f}") |
| 168 | + |
| 169 | + if rollout.violations: |
| 170 | + for v in rollout.violations: |
| 171 | + print(f" ⚠️ {v.policy_name}: {v.description}") |
| 172 | + |
| 173 | + # 5. Report final statistics |
| 174 | + print("\n" + "=" * 60) |
| 175 | + print("Training Summary") |
| 176 | + print("=" * 60) |
| 177 | + |
| 178 | + stats = runner.get_stats() |
| 179 | + reward_stats = reward_fn.get_stats() |
| 180 | + |
| 181 | + print(f"\nRunner Statistics:") |
| 182 | + print(f" Total rollouts: {stats['total_rollouts']}") |
| 183 | + print(f" Total violations: {stats['total_violations']}") |
| 184 | + print(f" Violation rate: {stats['violation_rate']:.1%}") |
| 185 | + |
| 186 | + print(f"\nReward Statistics:") |
| 187 | + print(f" Total reward: {total_reward:.2f}") |
| 188 | + print(f" Avg penalty: {reward_stats['avg_penalty']:.2f}") |
| 189 | + print(f" Clean rate: {reward_stats['clean_rate']:.1%}") |
| 190 | + |
| 191 | + print("\n" + "=" * 60) |
| 192 | + print("Key Insight: Agent learns that DROP/DELETE → negative reward") |
| 193 | + print("After training, agent will avoid dangerous SQL operations!") |
| 194 | + print("=" * 60) |
| 195 | + |
| 196 | + # Cleanup |
| 197 | + runner.teardown() |
| 198 | + |
| 199 | + |
| 200 | +async def demo_environment(): |
| 201 | + """Demonstrate the GovernedEnvironment.""" |
| 202 | + |
| 203 | + from agent_os.integrations.agent_lightning import ( |
| 204 | + GovernedEnvironment, |
| 205 | + EnvironmentConfig, |
| 206 | + ) |
| 207 | + |
| 208 | + print("\n" + "=" * 60) |
| 209 | + print("GovernedEnvironment Demo") |
| 210 | + print("=" * 60) |
| 211 | + |
| 212 | + kernel = MockKernelSpace() |
| 213 | + |
| 214 | + config = EnvironmentConfig( |
| 215 | + max_steps=10, |
| 216 | + violation_penalty=-10.0, |
| 217 | + terminate_on_critical=True, |
| 218 | + ) |
| 219 | + |
| 220 | + env = GovernedEnvironment(kernel, config=config) |
| 221 | + |
| 222 | + # Run episode |
| 223 | + state, info = env.reset() |
| 224 | + print(f"\nEpisode started. Policies: {info.get('kernel_policies', [])}") |
| 225 | + |
| 226 | + actions = ["SELECT * FROM users", "UPDATE users SET x=1", "DROP TABLE users"] |
| 227 | + |
| 228 | + for action in actions: |
| 229 | + if env.terminated: |
| 230 | + break |
| 231 | + |
| 232 | + state, reward, terminated, truncated, info = env.step(action) |
| 233 | + print(f"\nAction: {action[:30]}...") |
| 234 | + print(f" Reward: {reward:.2f}") |
| 235 | + print(f" Terminated: {terminated}") |
| 236 | + print(f" Violations: {len(info.get('violations', []))}") |
| 237 | + |
| 238 | + print(f"\nEnvironment Metrics:") |
| 239 | + metrics = env.get_metrics() |
| 240 | + for k, v in metrics.items(): |
| 241 | + if isinstance(v, float): |
| 242 | + print(f" {k}: {v:.2f}") |
| 243 | + else: |
| 244 | + print(f" {k}: {v}") |
| 245 | + |
| 246 | + env.close() |
| 247 | + |
| 248 | + |
| 249 | +if __name__ == "__main__": |
| 250 | + print("\n" + "=" * 60) |
| 251 | + print("Agent OS + Agent-Lightning Integration Demo") |
| 252 | + print("=" * 60 + "\n") |
| 253 | + |
| 254 | + # Run training demo |
| 255 | + asyncio.run(train_sql_agent()) |
| 256 | + |
| 257 | + # Run environment demo |
| 258 | + asyncio.run(demo_environment()) |
| 259 | + |
| 260 | + print("\n✅ Demo complete!") |
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