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CareFlow Nexus - Pharmacy Agent
Hugging Face Deployment Ready
This agent manages medication dispensing, inventory tracking, and prescription fulfillment
for the CareFlow Nexus hospital operating system.
"""
import asyncio
import json
import os
import uuid
from datetime import datetime, timedelta
from enum import Enum
from typing import Any, Dict, List, Literal, Optional
import google.generativeai as genai
import uvicorn
from fastapi import BackgroundTasks, FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse
from pydantic import BaseModel, Field
# ============================================================================
# Configuration
# ============================================================================
AGENT_VERSION = "1.0.0"
AGENT_NAME = "Pharmacy Agent"
AGENT_ID = "pharmacy-agent-001"
# Configure Gemini API
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
if GEMINI_API_KEY:
genai.configure(api_key=GEMINI_API_KEY)
gemini_model = genai.GenerativeModel("gemini-pro")
else:
gemini_model = None
print("⚠️ Warning: GEMINI_API_KEY not found. AI features will be disabled.")
# ============================================================================
# Data Models
# ============================================================================
class MedicationStatus(str, Enum):
PENDING = "pending"
IN_PROGRESS = "in_progress"
READY = "ready"
DISPENSED = "dispensed"
CANCELLED = "cancelled"
OUT_OF_STOCK = "out_of_stock"
class PrescriptionRequest(BaseModel):
prescription_id: Optional[str] = None
patient_id: str = Field(..., description="Patient identifier")
patient_name: str = Field(..., description="Patient name")
doctor_id: str = Field(..., description="Prescribing doctor ID")
medications: List[Dict[str, Any]] = Field(..., description="List of medications")
priority: Literal["low", "medium", "high", "urgent"] = "medium"
notes: Optional[str] = None
class Config:
json_schema_extra = {
"example": {
"patient_id": "P12345",
"patient_name": "John Doe",
"doctor_id": "D001",
"medications": [
{
"name": "Amoxicillin",
"dosage": "500mg",
"frequency": "3x daily",
"duration": "7 days",
"quantity": 21,
}
],
"priority": "high",
"notes": "Patient has penicillin allergy - verify alternative",
}
}
class InventoryItem(BaseModel):
medication_name: str
stock_quantity: int
unit: str = "units"
expiry_date: Optional[str] = None
reorder_level: int = 50
location: Optional[str] = None
class PrescriptionResponse(BaseModel):
prescription_id: str
status: MedicationStatus
patient_id: str
patient_name: str
medications: List[Dict[str, Any]]
estimated_time: Optional[str] = None
pharmacist_notes: Optional[str] = None
created_at: str
updated_at: str
class TaskStatusResponse(BaseModel):
task_id: str
status: Literal["pending", "in_progress", "completed", "failed"]
progress: int = Field(ge=0, le=100)
message: str
result: Optional[Dict[str, Any]] = None
created_at: str
updated_at: str
class HealthResponse(BaseModel):
status: Literal["healthy", "degraded", "unhealthy"]
agent: str
version: str
uptime_seconds: float
active_tasks: int
total_processed: int
timestamp: str
# ============================================================================
# In-Memory Storage (Replace with database in production)
# ============================================================================
prescriptions_db: Dict[str, Dict[str, Any]] = {}
tasks_db: Dict[str, Dict[str, Any]] = {}
inventory_db: Dict[str, InventoryItem] = {
"Amoxicillin": InventoryItem(
medication_name="Amoxicillin",
stock_quantity=500,
unit="tablets",
expiry_date="2025-12-31",
reorder_level=100,
location="A-12",
),
"Ibuprofen": InventoryItem(
medication_name="Ibuprofen",
stock_quantity=800,
unit="tablets",
expiry_date="2025-11-30",
reorder_level=150,
location="B-05",
),
"Paracetamol": InventoryItem(
medication_name="Paracetamol",
stock_quantity=1200,
unit="tablets",
expiry_date="2026-03-15",
reorder_level=200,
location="B-06",
),
"Insulin": InventoryItem(
medication_name="Insulin",
stock_quantity=75,
unit="vials",
expiry_date="2025-06-30",
reorder_level=20,
location="C-01-Refrigerated",
),
"Aspirin": InventoryItem(
medication_name="Aspirin",
stock_quantity=600,
unit="tablets",
expiry_date="2025-10-20",
reorder_level=100,
location="A-15",
),
}
# Agent statistics
agent_stats = {"start_time": datetime.now(), "total_processed": 0, "active_tasks": 0}
# ============================================================================
# FastAPI App
# ============================================================================
app = FastAPI(
title="CareFlow Nexus - Pharmacy Agent",
description="AI-powered medication management and dispensing agent",
version=AGENT_VERSION,
docs_url="/docs",
redoc_url="/redoc",
)
# CORS Configuration
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # Configure appropriately for production
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# ============================================================================
# Helper Functions
# ============================================================================
async def check_drug_interactions(medications: List[Dict[str, Any]]) -> Dict[str, Any]:
"""Use Gemini AI to check for potential drug interactions"""
if not gemini_model:
return {
"has_interactions": False,
"message": "AI check unavailable",
"warnings": [],
}
try:
med_names = [med.get("name", "") for med in medications]
prompt = f"""As a clinical pharmacist AI, analyze these medications for potential drug interactions:
Medications: {", ".join(med_names)}
Provide:
1. Any potential drug-drug interactions
2. Severity level (low/medium/high/critical)
3. Recommended actions or alternatives
4. Special monitoring requirements
Format response as JSON with keys: has_interactions (bool), severity (string), interactions (list), recommendations (list)"""
response = gemini_model.generate_content(prompt)
# Parse AI response
ai_analysis = {
"has_interactions": "interaction" in response.text.lower(),
"ai_response": response.text,
"checked_at": datetime.now().isoformat(),
}
return ai_analysis
except Exception as e:
return {
"has_interactions": False,
"error": str(e),
"warnings": ["AI check failed"],
}
async def generate_pharmacist_notes(prescription: Dict[str, Any]) -> str:
"""Use Gemini AI to generate professional pharmacist notes"""
if not gemini_model:
return "Prescription verified and approved for dispensing."
try:
prompt = f"""As a clinical pharmacist, provide brief professional notes for this prescription:
Patient: {prescription.get("patient_name")}
Medications: {json.dumps(prescription.get("medications", []), indent=2)}
Priority: {prescription.get("priority")}
Doctor's Notes: {prescription.get("notes", "None")}
Provide:
1. Key counseling points for the patient
2. Administration instructions
3. Important warnings or precautions
4. Storage requirements
Keep it concise (max 3-4 sentences)."""
response = gemini_model.generate_content(prompt)
return response.text.strip()
except Exception as e:
return f"Prescription approved. Standard counseling recommended. (AI note generation failed: {str(e)})"
def check_inventory(medications: List[Dict[str, Any]]) -> tuple[bool, List[str]]:
"""Check if all medications are in stock"""
out_of_stock = []
for med in medications:
med_name = med.get("name", "")
quantity = med.get("quantity", 0)
if med_name in inventory_db:
if inventory_db[med_name].stock_quantity < quantity:
out_of_stock.append(
f"{med_name} (need {quantity}, have {inventory_db[med_name].stock_quantity})"
)
else:
out_of_stock.append(f"{med_name} (not in inventory)")
return len(out_of_stock) == 0, out_of_stock
def update_inventory(medications: List[Dict[str, Any]]):
"""Update inventory after dispensing"""
for med in medications:
med_name = med.get("name", "")
quantity = med.get("quantity", 0)
if med_name in inventory_db:
inventory_db[med_name].stock_quantity -= quantity
async def process_prescription_task(prescription_id: str):
"""Background task to process prescription"""
try:
# Update task status
tasks_db[prescription_id]["status"] = "in_progress"
tasks_db[prescription_id]["progress"] = 10
tasks_db[prescription_id]["message"] = "Verifying prescription..."
await asyncio.sleep(1)
# AI-powered drug interaction check
prescription = prescriptions_db[prescription_id]
tasks_db[prescription_id]["progress"] = 20
tasks_db[prescription_id]["message"] = "Checking drug interactions with AI..."
interaction_check = await check_drug_interactions(prescription["medications"])
if interaction_check.get("has_interactions"):
prescriptions_db[prescription_id]["pharmacist_notes"] = (
f"⚠️ AI Alert: {interaction_check.get('ai_response', 'Potential interactions detected')}"
)
await asyncio.sleep(1)
# Check inventory
tasks_db[prescription_id]["progress"] = 30
tasks_db[prescription_id]["message"] = "Checking inventory..."
await asyncio.sleep(1)
# Check inventory
prescription = prescriptions_db[prescription_id]
in_stock, out_of_stock_items = check_inventory(prescription["medications"])
if not in_stock:
tasks_db[prescription_id]["status"] = "failed"
tasks_db[prescription_id]["progress"] = 100
tasks_db[prescription_id]["message"] = (
f"Out of stock: {', '.join(out_of_stock_items)}"
)
prescriptions_db[prescription_id]["status"] = MedicationStatus.OUT_OF_STOCK
prescriptions_db[prescription_id]["pharmacist_notes"] = (
f"Out of stock: {', '.join(out_of_stock_items)}"
)
return
# Simulate medication preparation
tasks_db[prescription_id]["progress"] = 50
tasks_db[prescription_id]["message"] = "Preparing medications..."
await asyncio.sleep(2)
tasks_db[prescription_id]["progress"] = 70
tasks_db[prescription_id]["message"] = "Labeling and packaging..."
await asyncio.sleep(1)
tasks_db[prescription_id]["progress"] = 90
tasks_db[prescription_id]["message"] = "Final quality check..."
await asyncio.sleep(1)
# Update inventory
update_inventory(prescription["medications"])
# Generate AI-powered pharmacist notes
tasks_db[prescription_id]["progress"] = 95
tasks_db[prescription_id]["message"] = "Generating counseling notes..."
ai_notes = await generate_pharmacist_notes(prescription)
if not prescriptions_db[prescription_id].get("pharmacist_notes"):
prescriptions_db[prescription_id]["pharmacist_notes"] = ai_notes
# Complete
tasks_db[prescription_id]["status"] = "completed"
tasks_db[prescription_id]["progress"] = 100
tasks_db[prescription_id]["message"] = "Prescription ready for pickup"
tasks_db[prescription_id]["result"] = {
"prescription_id": prescription_id,
"ready_time": datetime.now().isoformat(),
"ai_enhanced": gemini_model is not None,
}
prescriptions_db[prescription_id]["status"] = MedicationStatus.READY
prescriptions_db[prescription_id]["updated_at"] = datetime.now().isoformat()
agent_stats["total_processed"] += 1
agent_stats["active_tasks"] -= 1
except Exception as e:
tasks_db[prescription_id]["status"] = "failed"
tasks_db[prescription_id]["progress"] = 100
tasks_db[prescription_id]["message"] = f"Error: {str(e)}"
agent_stats["active_tasks"] -= 1
# ============================================================================
# API Endpoints
# ============================================================================
@app.get("/", tags=["General"])
async def root():
"""Root endpoint"""
return {
"agent": AGENT_NAME,
"version": AGENT_VERSION,
"status": "online",
"endpoints": {
"health": "/health",
"docs": "/docs",
"prescriptions": "/api/pharmacy/prescriptions",
"inventory": "/api/pharmacy/inventory",
},
}
@app.get("/health", response_model=HealthResponse, tags=["General"])
async def health_check():
"""Health check endpoint"""
uptime = (datetime.now() - agent_stats["start_time"]).total_seconds()
return HealthResponse(
status="healthy" if gemini_model else "degraded",
agent=AGENT_NAME,
version=AGENT_VERSION,
uptime_seconds=uptime,
active_tasks=agent_stats["active_tasks"],
total_processed=agent_stats["total_processed"],
timestamp=datetime.now().isoformat(),
)
@app.post(
"/api/pharmacy/prescriptions",
response_model=PrescriptionResponse,
tags=["Pharmacy"],
)
async def create_prescription(
request: PrescriptionRequest, background_tasks: BackgroundTasks
):
"""
Submit a new prescription for processing
The agent will:
1. Verify prescription details
2. Check inventory availability
3. Prepare medications
4. Package and label
5. Notify when ready for pickup
"""
# Generate prescription ID
prescription_id = request.prescription_id or f"RX-{uuid.uuid4().hex[:8].upper()}"
# Check if prescription already exists
if prescription_id in prescriptions_db:
raise HTTPException(status_code=400, detail="Prescription ID already exists")
# Quick inventory check
in_stock, out_of_stock_items = check_inventory(request.medications)
# Create prescription record
prescription = {
"prescription_id": prescription_id,
"status": MedicationStatus.PENDING
if in_stock
else MedicationStatus.OUT_OF_STOCK,
"patient_id": request.patient_id,
"patient_name": request.patient_name,
"doctor_id": request.doctor_id,
"medications": request.medications,
"priority": request.priority,
"notes": request.notes,
"estimated_time": (datetime.now() + timedelta(minutes=15)).isoformat()
if in_stock
else None,
"pharmacist_notes": None
if in_stock
else f"Out of stock: {', '.join(out_of_stock_items)}",
"created_at": datetime.now().isoformat(),
"updated_at": datetime.now().isoformat(),
}
prescriptions_db[prescription_id] = prescription
# Create task record
tasks_db[prescription_id] = {
"task_id": prescription_id,
"status": "pending" if in_stock else "failed",
"progress": 0 if in_stock else 100,
"message": "Prescription submitted"
if in_stock
else f"Out of stock: {', '.join(out_of_stock_items)}",
"result": None,
"created_at": datetime.now().isoformat(),
"updated_at": datetime.now().isoformat(),
}
# Start background processing if in stock
if in_stock:
agent_stats["active_tasks"] += 1
background_tasks.add_task(process_prescription_task, prescription_id)
return PrescriptionResponse(**prescription)
@app.get(
"/api/pharmacy/prescriptions/{prescription_id}",
response_model=PrescriptionResponse,
tags=["Pharmacy"],
)
async def get_prescription(prescription_id: str):
"""Get prescription status by ID"""
if prescription_id not in prescriptions_db:
raise HTTPException(status_code=404, detail="Prescription not found")
return PrescriptionResponse(**prescriptions_db[prescription_id])
@app.get(
"/api/pharmacy/prescriptions",
response_model=List[PrescriptionResponse],
tags=["Pharmacy"],
)
async def list_prescriptions(
status: Optional[MedicationStatus] = None,
patient_id: Optional[str] = None,
limit: int = 50,
):
"""List all prescriptions with optional filters"""
results = list(prescriptions_db.values())
if status:
results = [p for p in results if p["status"] == status]
if patient_id:
results = [p for p in results if p["patient_id"] == patient_id]
results = sorted(results, key=lambda x: x["created_at"], reverse=True)
results = results[:limit]
return [PrescriptionResponse(**p) for p in results]
@app.post("/api/pharmacy/prescriptions/{prescription_id}/dispense", tags=["Pharmacy"])
async def dispense_prescription(prescription_id: str):
"""Mark prescription as dispensed (picked up by patient)"""
if prescription_id not in prescriptions_db:
raise HTTPException(status_code=404, detail="Prescription not found")
prescription = prescriptions_db[prescription_id]
if prescription["status"] != MedicationStatus.READY:
raise HTTPException(
status_code=400,
detail=f"Prescription not ready for dispensing. Current status: {prescription['status']}",
)
prescription["status"] = MedicationStatus.DISPENSED
prescription["updated_at"] = datetime.now().isoformat()
return {
"message": "Prescription dispensed successfully",
"prescription_id": prescription_id,
"dispensed_at": prescription["updated_at"],
}
@app.post("/api/pharmacy/prescriptions/{prescription_id}/cancel", tags=["Pharmacy"])
async def cancel_prescription(prescription_id: str, reason: Optional[str] = None):
"""Cancel a prescription"""
if prescription_id not in prescriptions_db:
raise HTTPException(status_code=404, detail="Prescription not found")
prescription = prescriptions_db[prescription_id]
if prescription["status"] == MedicationStatus.DISPENSED:
raise HTTPException(
status_code=400, detail="Cannot cancel dispensed prescription"
)
prescription["status"] = MedicationStatus.CANCELLED
prescription["pharmacist_notes"] = f"Cancelled: {reason or 'No reason provided'}"
prescription["updated_at"] = datetime.now().isoformat()
return {
"message": "Prescription cancelled successfully",
"prescription_id": prescription_id,
}
@app.get(
"/api/pharmacy/inventory", response_model=List[InventoryItem], tags=["Pharmacy"]
)
async def get_inventory(low_stock_only: bool = False):
"""Get current medication inventory"""
items = list(inventory_db.values())
if low_stock_only:
items = [item for item in items if item.stock_quantity <= item.reorder_level]
return items
@app.put(
"/api/pharmacy/inventory/{medication_name}",
response_model=InventoryItem,
tags=["Pharmacy"],
)
async def update_inventory_item(medication_name: str, item: InventoryItem):
"""Update inventory for a medication"""
inventory_db[medication_name] = item
return item
@app.get(
"/api/pharmacy/tasks/{task_id}", response_model=TaskStatusResponse, tags=["Tasks"]
)
async def get_task_status(task_id: str):
"""Get task processing status"""
if task_id not in tasks_db:
raise HTTPException(status_code=404, detail="Task not found")
return TaskStatusResponse(**tasks_db[task_id])
@app.get("/api/pharmacy/stream/{prescription_id}", tags=["Streaming"])
async def stream_prescription_status(prescription_id: str):
"""
Server-Sent Events (SSE) endpoint for real-time prescription updates
"""
if prescription_id not in prescriptions_db:
raise HTTPException(status_code=404, detail="Prescription not found")
async def event_generator():
last_status = None
while True:
if prescription_id in tasks_db:
task = tasks_db[prescription_id]
current_status = task["status"]
# Send update if status changed
if current_status != last_status:
event_data = {
"prescription_id": prescription_id,
"status": task["status"],
"progress": task["progress"],
"message": task["message"],
"timestamp": datetime.now().isoformat(),
}
yield f"data: {json.dumps(event_data)}\n\n"
last_status = current_status
# Stop streaming if completed or failed
if current_status in ["completed", "failed"]:
break
await asyncio.sleep(1)
# Send final message
yield f"data: {json.dumps({'status': 'stream_ended'})}\n\n"
return StreamingResponse(
event_generator(),
media_type="text/event-stream",
headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
)
@app.get("/api/pharmacy/stats", tags=["Analytics"])
async def get_statistics():
"""Get pharmacy agent statistics"""
return {
"total_prescriptions": len(prescriptions_db),
"active_prescriptions": len(
[
p
for p in prescriptions_db.values()
if p["status"]
in [MedicationStatus.PENDING, MedicationStatus.IN_PROGRESS]
]
),
"completed_today": agent_stats["total_processed"],
"active_tasks": agent_stats["active_tasks"],
"inventory_items": len(inventory_db),
"low_stock_items": len(
[
item
for item in inventory_db.values()
if item.stock_quantity <= item.reorder_level
]
),
"uptime_seconds": (datetime.now() - agent_stats["start_time"]).total_seconds(),
"ai_enabled": gemini_model is not None,
"gemini_configured": GEMINI_API_KEY is not None,
}
@app.post("/api/pharmacy/ai/analyze", tags=["AI Features"])
async def ai_analyze_prescription(
patient_name: str,
medications: List[Dict[str, Any]],
medical_history: Optional[str] = None,
):
"""
Use Gemini AI to analyze prescription for potential issues
Provides:
- Drug interaction analysis
- Dosage recommendations
- Patient counseling points
- Safety warnings
"""
if not gemini_model:
raise HTTPException(
status_code=503,
detail="AI features unavailable. GEMINI_API_KEY not configured.",
)
try:
prompt = f"""As an expert clinical pharmacist AI, analyze this prescription:
Patient: {patient_name}
Medical History: {medical_history or "Not provided"}
Medications: {json.dumps(medications, indent=2)}
Provide comprehensive analysis:
1. Drug-drug interactions (if any)
2. Contraindications based on medical history
3. Dosage appropriateness
4. Patient counseling points
5. Monitoring recommendations
6. Safety warnings
Be specific and clinically relevant."""
response = gemini_model.generate_content(prompt)
# Check for interactions
interaction_check = await check_drug_interactions(medications)
return {
"success": True,
"analysis": response.text,
"interaction_check": interaction_check,
"timestamp": datetime.now().isoformat(),
"model": "gemini-pro",
}
except Exception as e:
raise HTTPException(status_code=500, detail=f"AI analysis failed: {str(e)}")
# ============================================================================
# Main Entry Point
# ============================================================================
if __name__ == "__main__":
port = int(os.environ.get("PORT", 7860)) # Hugging Face uses port 7860
uvicorn.run("app:app", host="0.0.0.0", port=port, reload=False, log_level="info")
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