Spaces:
Runtime error
Runtime error
File size: 6,408 Bytes
f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a 37f9507 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a f9459c0 f70ac6a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 | """
ActionExecutorAgent - Prepares actionable buttons for user
Determines what actions are available based on analysis context
"""
from typing import Dict
from .base import Agent, AgentConfig, AgentResult
import time
class ActionExecutorAgent(Agent):
"""
Prepares action buttons based on context.
Does NOT execute — just plans available actions.
Actual execution happens in /api/copilot/action endpoint.
"""
AVAILABLE_ACTIONS = {
"CREATE_CASE": {
"label": "Create Investigation Case",
"icon": "📁",
"category": "DIRECT_ACTION",
"requires_confirmation": False,
"priority": 1,
},
"GENERATE_STR": {
"label": "Generate STR Report (PDF)",
"icon": "📄",
"category": "DATA_ACTION",
"requires_confirmation": False,
"priority": 2,
},
"OPEN_STR_BUILDER": {
"label": "Open STR Builder",
"icon": "🔨",
"category": "NAVIGATION",
"requires_confirmation": False,
"priority": 3,
},
"VIEW_GRAPH": {
"label": "Open Network Graph",
"icon": "🕸",
"category": "NAVIGATION",
"requires_confirmation": False,
"priority": 4,
},
"ADD_NOTES": {
"label": "Add Investigation Notes",
"icon": "📝",
"category": "DIRECT_ACTION",
"requires_confirmation": False,
"priority": 7,
},
}
def __init__(self, api_pool):
config = AgentConfig(
name="ActionExecutorAgent",
model="llama-3.1-8b-instant",
temperature=0.0,
max_tokens=500,
timeout_ms=5000,
)
super().__init__(config, api_pool)
def _build_prompt(self, **inputs) -> str:
return ""
def _parse_response(self, response_text: str) -> Dict:
return {}
async def invoke(
self,
account_id: str = None,
intent: str = "GENERAL",
risk_assessment: Dict = None,
alert_data: Dict = None,
**kwargs,
) -> AgentResult:
"""Prepare list of actions to show user based on context."""
start_time = time.time()
try:
actions = []
risk_score = 0
risk_tier = "LOW"
if risk_assessment:
recommendation = risk_assessment.get("recommendation", {})
risk_tier = recommendation.get("priority", "MEDIUM")
if alert_data:
risk_score = alert_data.get("risk_score", 0)
risk_tier = alert_data.get("risk_tier", risk_tier)
is_high_risk = risk_tier == "CRITICAL"
is_medium_risk = risk_tier in ["HIGH", "MEDIUM"]
# Create case for medium/high risk accounts
if account_id and (is_high_risk or is_medium_risk):
actions.append(self._build_action("CREATE_CASE", {
"account_id": account_id,
"alert_id": alert_data.get("alert_id") if alert_data else None,
"description": f"Investigation for {account_id}",
"priority": "CRITICAL" if is_high_risk else "HIGH",
}))
# STR/SAR generation for NARRATIVE intent or high-risk
if account_id and (intent == "NARRATIVE" or is_high_risk):
actions.append(self._build_action("GENERATE_STR", {
"account_id": account_id,
"alert_id": alert_data.get("alert_id") if alert_data else None,
}))
actions.append(self._build_action("OPEN_STR_BUILDER", {
"account_id": account_id,
"url": f"#str-builder?account={account_id}",
}))
# Navigation — always available when account_id is known
if account_id:
actions.append(self._build_action("VIEW_GRAPH", {
"account_id": account_id,
"url": f"#investigation?account={account_id}",
"hops": 2,
"max_nodes": 50,
}))
# Add notes — only if a case exists (medium/high risk context)
if account_id and (is_high_risk or is_medium_risk):
actions.append(self._build_action("ADD_NOTES", {
"account_id": account_id,
"url": f"#cases?account={account_id}&action=new_note",
}))
actions.sort(key=lambda x: x.get("priority", 99))
result_data = {
"actions": actions,
"actions_count": len(actions),
"context_analyzed": {
"account_id": account_id,
"intent": intent,
"risk_score": risk_score,
"risk_tier": risk_tier,
},
}
self.logger.info(f"[OK] {self.config.name}: Prepared {len(actions)} actions")
return await self._create_result(
success=True,
data=result_data,
tokens_input=0,
tokens_output=0,
start_time=start_time,
)
except Exception as e:
self.logger.error(f"[FAIL] {self.config.name}: {e}")
return await self._create_result(
success=False,
data={"actions": []},
error=str(e),
start_time=start_time,
)
def _build_action(self, action_type: str, payload: Dict) -> Dict:
"""Build an action object with full metadata."""
if action_type not in self.AVAILABLE_ACTIONS:
return {}
cfg = self.AVAILABLE_ACTIONS[action_type]
return {
"id": f"action_{action_type.lower()}_{int(time.time() * 1000)}",
"type": action_type,
"label": cfg["label"],
"icon": cfg.get("icon", ""),
"category": cfg["category"],
"priority": cfg["priority"],
"requires_confirmation": cfg.get("requires_confirmation", False),
"confirmation_message": cfg.get("confirmation_message", ""),
"enabled": True,
"payload": payload,
}
|