File size: 21,471 Bytes
10fcca6 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 |
"""
Memory Agent (State Manager Agent) for CareFlow Nexus
Agent 1: Memorizes all hospital data and provides state queries
This agent is 50% rule-based (data queries, metrics) and 50% AI (analysis, bottleneck detection)
"""
import logging
from datetime import datetime, timedelta
from typing import Any, Dict, List, Optional
from base_agent import BaseAgent
from prompts.prompt_templates import StateManagerPrompts
from services.firebase_service import FirebaseService
from services.gemini_service import GeminiService
from utils.response_parser import ResponseParser
logger = logging.getLogger(__name__)
class MemoryAgent(BaseAgent):
"""
State Manager Agent - Memorizes and manages hospital state
Responsibilities:
- Load and cache all hospital data (beds, staff, patients, tasks)
- Provide fast queries to other agents
- Monitor system state in real-time
- Detect bottlenecks and anomalies (AI-powered)
- Generate state analysis reports (AI-powered)
"""
def __init__(
self,
firebase_service: FirebaseService,
gemini_service: GeminiService,
refresh_interval: int = 300, # 5 minutes
):
"""
Initialize Memory Agent
Args:
firebase_service: Firebase service instance
gemini_service: Gemini AI service instance
refresh_interval: How often to refresh state cache (seconds)
"""
super().__init__(
agent_id="memory_agent_001",
agent_type="state_manager",
firebase_service=firebase_service,
gemini_service=gemini_service,
)
self.refresh_interval = refresh_interval
self.state_cache = {
"beds": [],
"patients": [],
"staff": [],
"tasks": [],
"last_refresh": None,
}
self.logger.info("Memory Agent initialized")
async def initialize(self) -> bool:
"""
Initialize agent by loading all hospital data
Returns:
True if successful
"""
try:
self.logger.info("Initializing Memory Agent - loading hospital data...")
await self.refresh_state()
self.logger.info("Memory Agent initialization complete")
return True
except Exception as e:
self.logger.error(f"Failed to initialize Memory Agent: {e}")
return False
async def process(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
"""
Process incoming requests
Args:
request_data: Request with 'type' and optional parameters
Returns:
Response dictionary
"""
try:
request_type = request_data.get("type", "")
# Auto-refresh if cache is stale
await self._check_and_refresh()
# Route request to appropriate handler
if request_type == "get_available_beds":
result = await self.get_available_beds(request_data.get("filters"))
return self.format_response(True, result, "Available beds retrieved")
elif request_type == "get_patient_requirements":
patient_id = request_data.get("patient_id")
result = await self.get_patient_requirements(patient_id)
return self.format_response(
True, result, "Patient requirements retrieved"
)
elif request_type == "get_staff_availability":
role = request_data.get("role")
ward = request_data.get("ward")
result = await self.get_staff_availability(role, ward)
return self.format_response(
True, result, "Staff availability retrieved"
)
elif request_type == "get_system_state":
result = await self.get_system_state()
return self.format_response(True, result, "System state retrieved")
elif request_type == "analyze_state":
result = await self.analyze_state_with_ai()
return self.format_response(True, result, "State analysis complete")
elif request_type == "detect_bottlenecks":
result = await self.detect_bottlenecks()
return self.format_response(
True, result, "Bottleneck detection complete"
)
elif request_type == "get_metrics":
result = await self.get_metrics()
return self.format_response(True, result, "Metrics retrieved")
else:
return self.format_response(
False,
None,
f"Unknown request type: {request_type}",
"invalid_request",
)
except Exception as e:
self.logger.error(f"Error processing request: {e}")
await self.log_error(str(e), request_data, "process_error")
return self.format_response(False, None, str(e), "processing_error")
# ==================== RULE-BASED METHODS (50%) ====================
async def refresh_state(self) -> None:
"""Refresh entire hospital state from Firebase"""
try:
self.logger.info("Refreshing hospital state cache...")
# Load all data in parallel would be ideal, but we'll do sequential for simplicity
self.state_cache["beds"] = await self.firebase.get_all_beds()
self.state_cache["patients"] = await self.firebase.get_all_patients()
self.state_cache["staff"] = await self.firebase.get_all_staff()
self.state_cache["tasks"] = await self.firebase.get_tasks(
{"status": ["pending", "in_progress"]}
)
self.state_cache["last_refresh"] = datetime.now()
self.logger.info(
f"State refreshed - Beds: {len(self.state_cache['beds'])}, "
f"Patients: {len(self.state_cache['patients'])}, "
f"Staff: {len(self.state_cache['staff'])}, "
f"Tasks: {len(self.state_cache['tasks'])}"
)
except Exception as e:
self.logger.error(f"Error refreshing state: {e}")
raise
async def _check_and_refresh(self) -> None:
"""Check if cache is stale and refresh if needed"""
last_refresh = self.state_cache.get("last_refresh")
if last_refresh is None:
await self.refresh_state()
return
time_since_refresh = (datetime.now() - last_refresh).total_seconds()
if time_since_refresh > self.refresh_interval:
self.logger.info("Cache is stale, refreshing...")
await self.refresh_state()
async def get_available_beds(self, filters: Optional[Dict] = None) -> List[Dict]:
"""
Get available beds with optional filters (RULE-BASED)
Args:
filters: Optional filters like ward, has_oxygen, etc.
Returns:
List of available bed dictionaries
"""
beds = self.state_cache.get("beds", [])
available = [b for b in beds if b.get("status") == "ready"]
if not filters:
return available
# Apply filters
filtered = available
if "ward" in filters:
filtered = [b for b in filtered if b.get("ward") == filters["ward"]]
if "has_oxygen" in filters:
filtered = [
b
for b in filtered
if b.get("equipment", {}).get("has_oxygen") == filters["has_oxygen"]
]
if "has_ventilator" in filters:
filtered = [
b
for b in filtered
if b.get("equipment", {}).get("has_ventilator")
== filters["has_ventilator"]
]
if "is_isolation" in filters:
filtered = [
b
for b in filtered
if b.get("equipment", {}).get("is_isolation") == filters["is_isolation"]
]
if "floor" in filters:
filtered = [b for b in filtered if b.get("floor") == filters["floor"]]
self.logger.info(f"Found {len(filtered)} beds matching filters")
return filtered
async def get_patient_requirements(self, patient_id: str) -> Optional[Dict]:
"""
Get patient requirements (RULE-BASED)
Args:
patient_id: Patient ID
Returns:
Patient requirements dictionary or None
"""
patient = await self.firebase.get_patient(patient_id)
if not patient:
self.logger.warning(f"Patient {patient_id} not found")
return None
# Extract requirements
requirements = patient.get("requirements", {})
# Add diagnosis and severity for context
requirements["diagnosis"] = patient.get("diagnosis", "")
requirements["severity"] = patient.get("severity", "moderate")
requirements["mobility_status"] = patient.get("mobility_status", "ambulatory")
return requirements
async def get_staff_availability(
self, role: str, ward: Optional[str] = None
) -> List[Dict]:
"""
Get available staff by role and optional ward (RULE-BASED)
Args:
role: Staff role (nurse, cleaner, doctor)
ward: Optional ward filter
Returns:
List of available staff
"""
staff = self.state_cache.get("staff", [])
# Filter by role and on-shift
available = [
s
for s in staff
if s.get("role") == role
and s.get("is_on_shift", False)
and s.get("current_load", 0) < 5
]
# Filter by ward if specified
if ward:
available = [s for s in available if s.get("assigned_ward") == ward]
# Sort by workload (least busy first)
available.sort(key=lambda x: x.get("current_load", 0))
self.logger.info(f"Found {len(available)} available {role}s")
return available
async def get_system_state(self) -> Dict[str, Any]:
"""
Get complete system state snapshot (RULE-BASED)
Returns:
System state dictionary
"""
beds = self.state_cache.get("beds", [])
patients = self.state_cache.get("patients", [])
staff = self.state_cache.get("staff", [])
tasks = self.state_cache.get("tasks", [])
return {
"beds": {
"total": len(beds),
"available": len([b for b in beds if b["status"] == "ready"]),
"occupied": len([b for b in beds if b["status"] == "occupied"]),
"cleaning": len([b for b in beds if b["status"] == "cleaning"]),
"maintenance": len([b for b in beds if b["status"] == "maintenance"]),
},
"patients": {
"total": len(patients),
"waiting": len([p for p in patients if p.get("status") == "waiting"]),
"admitted": len([p for p in patients if p.get("status") == "admitted"]),
},
"staff": {
"total": len(staff),
"on_shift": len([s for s in staff if s.get("is_on_shift")]),
"nurses": len(
[s for s in staff if s["role"] == "nurse" and s.get("is_on_shift")]
),
"cleaners": len(
[
s
for s in staff
if s["role"] == "cleaner" and s.get("is_on_shift")
]
),
},
"tasks": {
"total": len(tasks),
"pending": len([t for t in tasks if t["status"] == "pending"]),
"in_progress": len([t for t in tasks if t["status"] == "in_progress"]),
},
"timestamp": datetime.now().isoformat(),
}
async def get_metrics(self) -> Dict[str, Any]:
"""
Get operational metrics (RULE-BASED)
Returns:
Metrics dictionary
"""
return await self.firebase.get_metrics()
# ==================== AI-POWERED METHODS (50%) ====================
async def analyze_state_with_ai(self) -> Dict[str, Any]:
"""
Use Gemini AI to analyze current hospital state (AI-POWERED)
Returns:
Analysis with alerts, bottlenecks, forecast, recommendations
"""
try:
self.logger.info("Running AI state analysis...")
# Prepare state summary
state = await self.get_system_state()
ward_summary = self._prepare_ward_summary()
# Build prompt
prompt = StateManagerPrompts.STATE_ANALYSIS.format(
total_beds=state["beds"]["total"],
available_beds=state["beds"]["available"],
occupied_beds=state["beds"]["occupied"],
cleaning_beds=state["beds"]["cleaning"],
maintenance_beds=state["beds"]["maintenance"],
utilization_rate=round(
(state["beds"]["occupied"] / state["beds"]["total"] * 100)
if state["beds"]["total"] > 0
else 0,
1,
),
total_patients=state["patients"]["total"],
waiting_patients=state["patients"]["waiting"],
admitted_patients=state["patients"]["admitted"],
nurses_count=state["staff"]["nurses"],
cleaners_count=state["staff"]["cleaners"],
total_staff=state["staff"]["on_shift"],
active_tasks=state["tasks"]["total"],
pending_tasks=state["tasks"]["pending"],
in_progress_tasks=state["tasks"]["in_progress"],
overdue_tasks=0, # TODO: Calculate overdue
ward_summary=ward_summary,
)
# Call Gemini AI
response = await self.gemini.generate_json_response(prompt, temperature=0.3)
# Parse response
if response:
parsed = ResponseParser.parse_state_analysis_response(response)
# Log decision
await self.log_decision(
action="state_analysis",
input_data={"state": state},
output_data=parsed,
reasoning="AI-powered state analysis completed",
)
return parsed
else:
self.logger.warning("Empty response from AI, returning default")
return self._default_analysis_response()
except Exception as e:
self.logger.error(f"Error in AI state analysis: {e}")
return self._default_analysis_response()
async def detect_bottlenecks(self) -> List[Dict[str, Any]]:
"""
Detect operational bottlenecks (HYBRID: Rule-based + AI)
Returns:
List of bottleneck dictionaries
"""
bottlenecks = []
# Rule-based detection
rule_bottlenecks = await self._detect_bottlenecks_rule_based()
bottlenecks.extend(rule_bottlenecks)
# AI-enhanced detection
if rule_bottlenecks:
ai_analysis = await self._detect_bottlenecks_ai()
if ai_analysis:
bottlenecks.extend(ai_analysis)
return bottlenecks
async def _detect_bottlenecks_rule_based(self) -> List[Dict[str, Any]]:
"""Rule-based bottleneck detection"""
bottlenecks = []
beds = self.state_cache.get("beds", [])
staff = self.state_cache.get("staff", [])
tasks = self.state_cache.get("tasks", [])
# Check cleaning backlog
cleaning_tasks = [
t
for t in tasks
if t.get("task_type") == "cleaning" and t["status"] == "pending"
]
if len(cleaning_tasks) > 5:
severity = (
"critical"
if len(cleaning_tasks) > 10
else "high"
if len(cleaning_tasks) > 7
else "medium"
)
bottlenecks.append(
{
"type": "cleaning_backlog",
"severity": severity,
"count": len(cleaning_tasks),
"description": f"{len(cleaning_tasks)} cleaning tasks pending",
"recommendation": "Assign more cleaners or prioritize critical cleaning tasks",
}
)
# Check staff overload
overloaded_staff = [s for s in staff if s.get("current_load", 0) >= 5]
if len(overloaded_staff) > 0:
bottlenecks.append(
{
"type": "staff_overload",
"severity": "high" if len(overloaded_staff) > 3 else "medium",
"count": len(overloaded_staff),
"description": f"{len(overloaded_staff)} staff members at maximum workload",
"recommendation": "Redistribute tasks or call additional staff",
}
)
# Check bed capacity
available_beds = [b for b in beds if b["status"] == "ready"]
total_beds = len(beds)
availability_rate = (
(len(available_beds) / total_beds * 100) if total_beds > 0 else 0
)
if availability_rate < 10:
bottlenecks.append(
{
"type": "critical_capacity",
"severity": "critical",
"count": len(available_beds),
"description": f"Only {len(available_beds)} beds available ({availability_rate:.1f}%)",
"recommendation": "Expedite discharges and cleaning tasks urgently",
}
)
elif availability_rate < 20:
bottlenecks.append(
{
"type": "low_capacity",
"severity": "high",
"count": len(available_beds),
"description": f"Low bed availability: {len(available_beds)} beds ({availability_rate:.1f}%)",
"recommendation": "Monitor closely and prepare for capacity issues",
}
)
return bottlenecks
async def _detect_bottlenecks_ai(self) -> List[Dict[str, Any]]:
"""AI-powered bottleneck detection for complex patterns"""
try:
state = await self.get_system_state()
response = await self.gemini.detect_bottlenecks(state)
if response and "bottlenecks" in response:
return response["bottlenecks"]
return []
except Exception as e:
self.logger.error(f"Error in AI bottleneck detection: {e}")
return []
def _prepare_ward_summary(self) -> str:
"""Prepare ward-level summary for prompts"""
beds = self.state_cache.get("beds", [])
wards = {}
for bed in beds:
ward = bed.get("ward", "Unknown")
if ward not in wards:
wards[ward] = {"total": 0, "available": 0, "occupied": 0}
wards[ward]["total"] += 1
if bed["status"] == "ready":
wards[ward]["available"] += 1
elif bed["status"] == "occupied":
wards[ward]["occupied"] += 1
summary_lines = []
for ward, stats in wards.items():
occupancy = (
(stats["occupied"] / stats["total"] * 100) if stats["total"] > 0 else 0
)
summary_lines.append(
f" - {ward}: {stats['available']}/{stats['total']} available ({occupancy:.0f}% occupied)"
)
return "\n".join(summary_lines) if summary_lines else " No ward data available"
def _default_analysis_response(self) -> Dict[str, Any]:
"""Default response when AI fails"""
return {
"critical_alerts": [],
"bottlenecks": [],
"capacity_forecast": {
"next_4_hours": "Unable to generate forecast",
"bed_availability_trend": "stable",
"staffing_adequacy": "unknown",
},
"recommendations": ["Refresh data and try again"],
}
def get_capabilities(self) -> List[str]:
"""Get agent capabilities"""
return [
"get_available_beds",
"get_patient_requirements",
"get_staff_availability",
"get_system_state",
"analyze_state",
"detect_bottlenecks",
"get_metrics",
]
|