2121 lines
87 KiB
Python
2121 lines
87 KiB
Python
"""
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Complaints Celery tasks
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This module contains tasks for:
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- Checking overdue complaints
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- Sending SLA reminders
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- Triggering resolution satisfaction surveys
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- Creating PX actions from complaints
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- AI-powered complaint analysis
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"""
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import logging
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from typing import Optional, Dict, Any, Tuple
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from celery import shared_task
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from django.db import transaction
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from django.db.models import Q
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from django.utils import timezone
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logger = logging.getLogger(__name__)
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def match_staff_from_name(staff_name: str, hospital_id: str, department_name: Optional[str] = None, return_all: bool = False, fuzzy_threshold: float = 0.65) -> Tuple[list, float, str]:
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"""
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Enhanced staff matching with fuzzy matching and improved accuracy.
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This function uses fuzzy string matching (Levenshtein distance) to find staff members
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with improved handling of:
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- Name variations (with/without hyphens, different spellings)
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- Typos and minor errors
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- Matching against original full name field
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- Better confidence scoring
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Args:
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staff_name: Name extracted from complaint (without titles)
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hospital_id: Hospital ID to search within
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department_name: Optional department name to prioritize matching
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return_all: If True, return all matching staff. If False, return single best match.
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fuzzy_threshold: Minimum similarity ratio for fuzzy matches (0.0 to 1.0)
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Returns:
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If return_all=True: Tuple of (matches_list, confidence_score, matching_method)
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- matches_list: List of dicts with matched staff details
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- confidence_score: Float from 0.0 to 1.0 (best match confidence)
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- matching_method: Description of how staff was matched
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If return_all=False: Tuple of (staff_id, confidence_score, matching_method)
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- staff_id: UUID of matched staff or None
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- confidence_score: Float from 0.0 to 1.0
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- matching_method: Description of how staff was matched
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"""
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from apps.organizations.models import Staff, Department
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if not staff_name or not staff_name.strip():
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return [], 0.0, "No staff name provided"
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staff_name = staff_name.strip()
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normalized_input = _normalize_name(staff_name)
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matches = []
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# Build base query - staff from this hospital, active status
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base_query = Staff.objects.filter(
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hospital_id=hospital_id,
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status='active'
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)
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# Get department if specified
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dept_id = None
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if department_name:
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department = Department.objects.filter(
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hospital_id=hospital_id,
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name__iexact=department_name,
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status='active'
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).first()
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if department:
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dept_id = department.id
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# Fetch all staff to perform fuzzy matching
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all_staff = list(base_query)
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# If department specified, filter
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if dept_id:
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dept_staff = [s for s in all_staff if str(s.department.id) == dept_id if s.department]
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else:
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dept_staff = []
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# ========================================
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# LAYER 1: EXACT MATCHES
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# ========================================
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# 1a. Exact match on first_name + last_name (English)
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words = staff_name.split()
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if len(words) >= 2:
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first_name = words[0]
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last_name = ' '.join(words[1:])
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for staff in all_staff:
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if staff.first_name.lower() == first_name.lower() and \
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staff.last_name.lower() == last_name.lower():
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confidence = 0.95 if (dept_id and staff.department and str(staff.department.id) == dept_id) else 0.90
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method = f"Exact English match in {'correct' if (dept_id and staff.department and str(staff.department.id) == dept_id) else 'any'} department"
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if not any(m['id'] == str(staff.id) for m in matches):
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matches.append(_create_match_dict(staff, confidence, method, staff_name))
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logger.info(f"EXACT MATCH (EN): {staff.first_name} {staff.last_name} == {first_name} {last_name}")
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# 1b. Exact match on full Arabic name
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for staff in all_staff:
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full_arabic = f"{staff.first_name_ar} {staff.last_name_ar}".strip()
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if full_arabic == staff_name:
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confidence = 0.95 if (dept_id and staff.department and str(staff.department.id) == dept_id) else 0.90
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method = f"Exact Arabic match in {'correct' if (dept_id and staff.department and str(staff.department.id) == dept_id) else 'any'} department"
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if not any(m['id'] == str(staff.id) for m in matches):
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matches.append(_create_match_dict(staff, confidence, method, staff_name))
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logger.info(f"EXACT MATCH (AR): {full_arabic} == {staff_name}")
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# 1c. Exact match on 'name' field (original full name)
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for staff in all_staff:
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if staff.name and staff.name.lower() == staff_name.lower():
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confidence = 0.93
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method = "Exact match on original name field"
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if not any(m['id'] == str(staff.id) for m in matches):
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matches.append(_create_match_dict(staff, confidence, method, staff_name))
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logger.info(f"EXACT MATCH (name field): {staff.name} == {staff_name}")
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# ========================================
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# LAYER 2: FUZZY MATCHES (if no exact)
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# ========================================
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if not matches:
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logger.info(f"No exact matches found, trying fuzzy matching for: {staff_name}")
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for staff in all_staff:
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# Try different name combinations
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name_combinations = [
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f"{staff.first_name} {staff.last_name}",
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f"{staff.first_name_ar} {staff.last_name_ar}",
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staff.name or "",
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staff.first_name,
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staff.last_name,
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staff.first_name_ar,
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staff.last_name_ar
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]
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# Check if any combination matches fuzzily
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best_ratio = 0.0
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best_match_name = ""
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for combo in name_combinations:
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if not combo:
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continue
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ratio = _fuzzy_match_ratio(staff_name, combo)
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if ratio > best_ratio:
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best_ratio = ratio
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best_match_name = combo
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# If good fuzzy match found
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if best_ratio >= fuzzy_threshold:
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# Adjust confidence based on match quality and department
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dept_bonus = 0.05 if (dept_id and staff.department and str(staff.department.id) == dept_id) else 0.0
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confidence = best_ratio * 0.85 + dept_bonus # Scale down slightly for fuzzy
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method = f"Fuzzy match ({best_ratio:.2f}) on '{best_match_name}'"
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if not any(m['id'] == str(staff.id) for m in matches):
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matches.append(_create_match_dict(staff, confidence, method, staff_name))
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logger.info(f"FUZZY MATCH ({best_ratio:.2f}): {best_match_name} ~ {staff_name}")
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# ========================================
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# LAYER 3: PARTIAL/WORD MATCHES
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# ========================================
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if not matches:
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logger.info(f"No fuzzy matches found, trying partial/word matching for: {staff_name}")
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# Split input name into words
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input_words = [_normalize_name(w) for w in staff_name.split() if _normalize_name(w)]
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for staff in all_staff:
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# Build list of all name fields
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staff_names = [
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staff.first_name,
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staff.last_name,
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staff.first_name_ar,
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staff.last_name_ar,
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staff.name or ""
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]
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# Count word matches
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match_count = 0
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total_words = len(input_words)
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for word in input_words:
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word_matched = False
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for staff_name_field in staff_names:
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if _normalize_name(staff_name_field) == word or \
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word in _normalize_name(staff_name_field):
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word_matched = True
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break
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if word_matched:
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match_count += 1
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# If at least 2 words match (or all if only 2 words)
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if match_count >= 2 or (total_words == 2 and match_count == 2):
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confidence = 0.60 + (match_count / total_words) * 0.15
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dept_bonus = 0.05 if (dept_id and staff.department and str(staff.department.id) == dept_id) else 0.0
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confidence += dept_bonus
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method = f"Partial match ({match_count}/{total_words} words)"
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if not any(m['id'] == str(staff.id) for m in matches):
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matches.append(_create_match_dict(staff, confidence, method, staff_name))
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logger.info(f"PARTIAL MATCH ({match_count}/{total_words}): {staff.first_name} {staff.last_name}")
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# ========================================
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# FINAL: SORT AND RETURN
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# ========================================
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if matches:
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# Sort by confidence (descending)
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matches.sort(key=lambda x: x['confidence'], reverse=True)
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best_confidence = matches[0]['confidence']
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best_method = matches[0]['matching_method']
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logger.info(
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f"Returning {len(matches)} match(es) for '{staff_name}'. "
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f"Best: {matches[0]['name_en']} (confidence: {best_confidence:.2f}, method: {best_method})"
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)
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if not return_all:
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return str(matches[0]['id']), best_confidence, best_method
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else:
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return matches, best_confidence, best_method
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else:
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logger.warning(f"No staff match found for name: '{staff_name}'")
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return [], 0.0, "No match found"
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def _fuzzy_match_ratio(str1: str, str2: str) -> float:
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"""
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Calculate fuzzy match ratio using difflib.
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Args:
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str1: First string
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str2: Second string
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Returns:
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Float from 0.0 to 1.0 representing similarity
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"""
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try:
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from difflib import SequenceMatcher
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return SequenceMatcher(None, str1.lower(), str2.lower()).ratio()
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except Exception:
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return 0.0
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def _normalize_name(name: str) -> str:
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"""
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Normalize name for better matching.
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- Remove extra spaces
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- Remove hyphens (Al-Shammari -> AlShammari)
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- Convert to lowercase
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- Remove common titles
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"""
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if not name:
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return ""
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name = name.strip().lower()
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# Remove common titles (both English and Arabic)
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titles = ['dr.', 'dr', 'mr.', 'mr', 'mrs.', 'mrs', 'ms.', 'ms',
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'د.', 'السيد', 'السيدة', 'الدكتور']
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for title in titles:
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if name.startswith(title):
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name = name[len(title):].strip()
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# Remove hyphens for better matching (Al-Shammari -> AlShammari)
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name = name.replace('-', '')
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# Remove extra spaces
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while ' ' in name:
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name = name.replace(' ', ' ')
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return name.strip()
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def _create_match_dict(staff, confidence: float, method: str, source_name: str) -> Dict[str, Any]:
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"""
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Create a match dictionary for a staff member.
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Args:
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staff: Staff model instance
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confidence: Confidence score (0.0 to 1.0)
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method: Description of matching method
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source_name: Original input name that was matched
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Returns:
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Dictionary with match details
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"""
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return {
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'id': str(staff.id),
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'name_en': f"{staff.first_name} {staff.last_name}",
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'name_ar': f"{staff.first_name_ar} {staff.last_name_ar}" if staff.first_name_ar and staff.last_name_ar else "",
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'original_name': staff.name or "",
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'job_title': staff.job_title,
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'specialization': staff.specialization,
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'department': staff.department.name if staff.department else None,
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'department_id': str(staff.department.id) if staff.department else None,
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'confidence': confidence,
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'matching_method': method,
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'source_name': source_name
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}
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@shared_task
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def check_overdue_complaints():
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"""
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Periodic task to check for overdue complaints.
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Runs every 15 minutes (configured in config/celery.py).
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Updates is_overdue flag for complaints past their SLA deadline.
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Triggers automatic escalation based on escalation rules.
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"""
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from apps.complaints.models import Complaint, ComplaintStatus
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# Get active complaints (not closed or cancelled)
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active_complaints = Complaint.objects.filter(
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status__in=[ComplaintStatus.OPEN, ComplaintStatus.IN_PROGRESS, ComplaintStatus.RESOLVED]
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).select_related('hospital', 'patient', 'department')
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overdue_count = 0
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escalated_count = 0
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for complaint in active_complaints:
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if complaint.check_overdue():
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overdue_count += 1
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logger.warning(
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f"Complaint {complaint.id} is overdue: {complaint.title} "
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f"(due: {complaint.due_at})"
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)
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# Trigger automatic escalation
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result = escalate_complaint_auto.delay(str(complaint.id))
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if result:
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escalated_count += 1
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if overdue_count > 0:
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logger.info(f"Found {overdue_count} overdue complaints, triggered {escalated_count} escalations")
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return {
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'overdue_count': overdue_count,
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'escalated_count': escalated_count
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}
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@shared_task
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def send_complaint_resolution_survey(complaint_id):
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"""
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Send resolution satisfaction survey when complaint is closed.
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This task is triggered when a complaint status changes to CLOSED.
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Args:
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complaint_id: UUID of the Complaint
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Returns:
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dict: Result with survey_instance_id
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"""
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from apps.complaints.models import Complaint
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from apps.core.services import create_audit_log
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from apps.surveys.models import SurveyInstance, SurveyTemplate
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try:
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complaint = Complaint.objects.select_related(
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'patient', 'hospital'
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).get(id=complaint_id)
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# Check if survey already sent
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if complaint.resolution_survey:
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logger.info(f"Resolution survey already sent for complaint {complaint_id}")
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return {'status': 'skipped', 'reason': 'already_sent'}
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# Get resolution satisfaction survey template
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try:
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survey_template = SurveyTemplate.objects.get(
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hospital=complaint.hospital,
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survey_type='complaint_resolution',
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is_active=True
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)
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except SurveyTemplate.DoesNotExist:
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logger.warning(
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f"No resolution satisfaction survey template found for hospital {complaint.hospital.name}"
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)
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return {'status': 'skipped', 'reason': 'no_template'}
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# Create survey instance
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with transaction.atomic():
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survey_instance = SurveyInstance.objects.create(
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survey_template=survey_template,
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patient=complaint.patient,
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encounter_id=complaint.encounter_id,
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delivery_channel='sms', # Default
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recipient_phone=complaint.patient.phone,
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recipient_email=complaint.patient.email,
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metadata={
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'complaint_id': str(complaint.id),
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'complaint_title': complaint.title
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}
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)
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# Link survey to complaint
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complaint.resolution_survey = survey_instance
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complaint.resolution_survey_sent_at = timezone.now()
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complaint.save(update_fields=['resolution_survey', 'resolution_survey_sent_at'])
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# Send survey
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from apps.notifications.services import NotificationService
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notification_log = NotificationService.send_survey_invitation(
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survey_instance=survey_instance,
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language='en' # TODO: Get from patient preference
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)
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# Update survey status
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survey_instance.status = 'active'
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survey_instance.sent_at = timezone.now()
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survey_instance.save(update_fields=['status', 'sent_at'])
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# Log audit event
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create_audit_log(
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event_type='survey_sent',
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description=f"Resolution satisfaction survey sent for complaint: {complaint.title}",
|
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content_object=survey_instance,
|
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metadata={
|
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'complaint_id': str(complaint.id),
|
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'survey_template': survey_template.name
|
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}
|
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)
|
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logger.info(
|
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f"Resolution satisfaction survey sent for complaint {complaint.id}"
|
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)
|
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|
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return {
|
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'status': 'sent',
|
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'survey_instance_id': str(survey_instance.id),
|
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'notification_log_id': str(notification_log.id)
|
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}
|
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|
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except Complaint.DoesNotExist:
|
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error_msg = f"Complaint {complaint_id} not found"
|
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logger.error(error_msg)
|
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return {'status': 'error', 'reason': error_msg}
|
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|
|
except Exception as e:
|
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error_msg = f"Error sending resolution survey: {str(e)}"
|
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logger.error(error_msg, exc_info=True)
|
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return {'status': 'error', 'reason': error_msg}
|
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|
|
|
|
@shared_task
|
|
def check_resolution_survey_threshold(survey_instance_id, complaint_id):
|
|
"""
|
|
Check if resolution survey score breaches threshold and create PX Action if needed.
|
|
|
|
This task is triggered when a complaint resolution survey is completed.
|
|
|
|
Args:
|
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survey_instance_id: UUID of the SurveyInstance
|
|
complaint_id: UUID of the Complaint
|
|
|
|
Returns:
|
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dict: Result with action status
|
|
"""
|
|
from apps.complaints.models import Complaint, ComplaintThreshold
|
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from apps.surveys.models import SurveyInstance
|
|
from apps.px_action_center.models import PXAction
|
|
from django.contrib.contenttypes.models import ContentType
|
|
|
|
try:
|
|
survey = SurveyInstance.objects.get(id=survey_instance_id)
|
|
complaint = Complaint.objects.select_related('hospital', 'patient').get(id=complaint_id)
|
|
|
|
# Get threshold for this hospital
|
|
try:
|
|
threshold = ComplaintThreshold.objects.get(
|
|
hospital=complaint.hospital,
|
|
threshold_type='resolution_survey_score',
|
|
is_active=True
|
|
)
|
|
except ComplaintThreshold.DoesNotExist:
|
|
logger.info(f"No resolution survey threshold configured for hospital {complaint.hospital.name_en}")
|
|
return {'status': 'no_threshold'}
|
|
|
|
# Check if threshold is breached
|
|
if threshold.check_threshold(survey.score):
|
|
logger.warning(
|
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f"Resolution survey score {survey.score} breaches threshold {threshold.threshold_value} "
|
|
f"for complaint {complaint_id}"
|
|
)
|
|
|
|
# Create PX Action
|
|
complaint_ct = ContentType.objects.get_for_model(Complaint)
|
|
|
|
action = PXAction.objects.create(
|
|
title=f"Low Resolution Satisfaction: {complaint.title[:100]}",
|
|
description=(
|
|
f"Complaint resolution survey scored {survey.score}% "
|
|
f"(threshold: {threshold.threshold_value}%). "
|
|
f"Original complaint: {complaint.description[:200]}"
|
|
),
|
|
source='complaint_resolution_survey',
|
|
priority='high' if survey.score < 30 else 'medium',
|
|
hospital=complaint.hospital,
|
|
department=complaint.department,
|
|
patient=complaint.patient,
|
|
content_type=complaint_ct,
|
|
object_id=complaint.id,
|
|
metadata={
|
|
'complaint_id': str(complaint.id),
|
|
'survey_id': str(survey.id),
|
|
'survey_score': survey.score,
|
|
'threshold_value': threshold.threshold_value,
|
|
}
|
|
)
|
|
|
|
# Log audit
|
|
from apps.core.services import create_audit_log
|
|
create_audit_log(
|
|
event_type='px_action_created',
|
|
description=f"PX Action created from low resolution survey score",
|
|
content_object=action,
|
|
metadata={
|
|
'complaint_id': str(complaint.id),
|
|
'survey_score': survey.score,
|
|
'trigger': 'resolution_survey_threshold'
|
|
}
|
|
)
|
|
|
|
logger.info(f"Created PX Action {action.id} from low resolution survey score")
|
|
|
|
return {
|
|
'status': 'action_created',
|
|
'action_id': str(action.id),
|
|
'survey_score': survey.score,
|
|
'threshold': threshold.threshold_value
|
|
}
|
|
else:
|
|
logger.info(f"Resolution survey score {survey.score} is above threshold {threshold.threshold_value}")
|
|
return {'status': 'threshold_not_breached', 'survey_score': survey.score}
|
|
|
|
except SurveyInstance.DoesNotExist:
|
|
error_msg = f"SurveyInstance {survey_instance_id} not found"
|
|
logger.error(error_msg)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
except Complaint.DoesNotExist:
|
|
error_msg = f"Complaint {complaint_id} not found"
|
|
logger.error(error_msg)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
except Exception as e:
|
|
error_msg = f"Error checking resolution survey threshold: {str(e)}"
|
|
logger.error(error_msg, exc_info=True)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
|
|
|
|
@shared_task
|
|
def create_action_from_complaint(complaint_id):
|
|
"""
|
|
Create PX Action from complaint (if configured).
|
|
|
|
This task is triggered when a complaint is created,
|
|
if the hospital configuration requires automatic action creation.
|
|
|
|
Args:
|
|
complaint_id: UUID of the Complaint
|
|
|
|
Returns:
|
|
dict: Result with action_id
|
|
"""
|
|
from apps.complaints.models import Complaint
|
|
from apps.organizations.models import Hospital
|
|
from apps.px_action_center.models import PXAction
|
|
from django.contrib.contenttypes.models import ContentType
|
|
|
|
try:
|
|
complaint = Complaint.objects.select_related('hospital', 'patient', 'department').get(id=complaint_id)
|
|
|
|
# Check if hospital has auto-create enabled
|
|
# For now, we'll check metadata on hospital or use a simple rule
|
|
# In production, you'd have a HospitalComplaintConfig model
|
|
# Handle case where metadata field might not exist (legacy data)
|
|
hospital_metadata = getattr(complaint.hospital, 'metadata', None)
|
|
if hospital_metadata is None:
|
|
hospital_metadata = {}
|
|
auto_create = hospital_metadata.get('auto_create_action_on_complaint', False)
|
|
|
|
if not auto_create:
|
|
logger.info(f"Auto-create PX Action disabled for hospital {complaint.hospital.name}")
|
|
return {'status': 'disabled'}
|
|
|
|
# Use JSON-serializable values instead of model objects
|
|
category_name = complaint.category.name_en if complaint.category else None
|
|
category_id = str(complaint.category.id) if complaint.category else None
|
|
|
|
# Create PX Action
|
|
complaint_ct = ContentType.objects.get_for_model(Complaint)
|
|
|
|
action = PXAction.objects.create(
|
|
title=f"New Complaint: {complaint.title[:100]}",
|
|
description=complaint.description[:500],
|
|
source='complaint',
|
|
priority=complaint.priority,
|
|
hospital=complaint.hospital,
|
|
department=complaint.department,
|
|
patient=complaint.patient,
|
|
content_type=complaint_ct,
|
|
object_id=complaint.id,
|
|
metadata={
|
|
'complaint_id': str(complaint.id),
|
|
'complaint_category': category_name,
|
|
'complaint_category_id': category_id,
|
|
'complaint_severity': complaint.severity,
|
|
}
|
|
)
|
|
|
|
# Log audit
|
|
from apps.core.services import create_audit_log
|
|
create_audit_log(
|
|
event_type='px_action_created',
|
|
description=f"PX Action created from complaint",
|
|
content_object=action,
|
|
metadata={
|
|
'complaint_id': str(complaint.id),
|
|
'trigger': 'complaint_creation'
|
|
}
|
|
)
|
|
|
|
logger.info(f"Created PX Action {action.id} from complaint {complaint_id}")
|
|
|
|
return {
|
|
'status': 'action_created',
|
|
'action_id': str(action.id)
|
|
}
|
|
|
|
except Complaint.DoesNotExist:
|
|
error_msg = f"Complaint {complaint_id} not found"
|
|
logger.error(error_msg)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
except Exception as e:
|
|
error_msg = f"Error creating action from complaint: {str(e)}"
|
|
logger.error(error_msg, exc_info=True)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
|
|
|
|
@shared_task
|
|
def escalate_complaint_auto(complaint_id):
|
|
"""
|
|
Automatically escalate complaint based on escalation rules.
|
|
|
|
This task is triggered when a complaint becomes overdue.
|
|
It finds matching escalation rules and reassigns the complaint.
|
|
Supports multi-level escalation with tracking.
|
|
|
|
Args:
|
|
complaint_id: UUID of the Complaint
|
|
|
|
Returns:
|
|
dict: Result with escalation status
|
|
"""
|
|
from apps.complaints.models import Complaint, ComplaintUpdate, EscalationRule
|
|
from apps.accounts.models import User
|
|
|
|
try:
|
|
complaint = Complaint.objects.select_related(
|
|
'hospital', 'department', 'assigned_to'
|
|
).get(id=complaint_id)
|
|
|
|
# Get current escalation level from metadata
|
|
current_level = complaint.metadata.get('escalation_level', 0)
|
|
|
|
# Calculate hours overdue
|
|
hours_overdue = (timezone.now() - complaint.due_at).total_seconds() / 3600
|
|
|
|
# Get applicable escalation rules for this hospital, ordered by escalation_level
|
|
rules = EscalationRule.objects.filter(
|
|
hospital=complaint.hospital,
|
|
is_active=True,
|
|
trigger_on_overdue=True
|
|
).order_by('escalation_level', 'order')
|
|
|
|
# Filter rules by severity and priority if specified
|
|
if complaint.severity:
|
|
rules = rules.filter(
|
|
Q(severity_filter='') | Q(severity_filter=complaint.severity)
|
|
)
|
|
|
|
if complaint.priority:
|
|
rules = rules.filter(
|
|
Q(priority_filter='') | Q(priority_filter=complaint.priority)
|
|
)
|
|
|
|
# Find matching rule for next escalation level
|
|
matching_rule = None
|
|
for rule in rules:
|
|
# Check if this is the next escalation level
|
|
if rule.escalation_level == current_level + 1:
|
|
# Check if we've exceeded trigger hours
|
|
if hours_overdue >= rule.trigger_hours_overdue:
|
|
# Check if we've exceeded max level
|
|
max_level = rule.max_escalation_level
|
|
if current_level >= max_level:
|
|
logger.info(
|
|
f"Complaint {complaint_id} has reached max escalation level {max_level}"
|
|
)
|
|
return {
|
|
'status': 'max_level_reached',
|
|
'max_level': max_level,
|
|
'current_level': current_level
|
|
}
|
|
matching_rule = rule
|
|
break
|
|
|
|
if not matching_rule:
|
|
logger.info(
|
|
f"No matching escalation rule found for complaint {complaint_id} "
|
|
f"(current level: {current_level}, hours overdue: {hours_overdue:.1f})"
|
|
)
|
|
return {'status': 'no_matching_rule', 'current_level': current_level}
|
|
|
|
# Determine escalation target
|
|
escalation_target = None
|
|
|
|
if matching_rule.escalate_to_role == 'department_manager':
|
|
if complaint.department and complaint.department.manager:
|
|
escalation_target = complaint.department.manager
|
|
|
|
elif matching_rule.escalate_to_role == 'hospital_admin':
|
|
# Find hospital admin for this hospital
|
|
escalation_target = User.objects.filter(
|
|
hospital=complaint.hospital,
|
|
groups__name='Hospital Admin',
|
|
is_active=True
|
|
).first()
|
|
|
|
elif matching_rule.escalate_to_role == 'px_admin':
|
|
# Find PX admin
|
|
escalation_target = User.objects.filter(
|
|
groups__name='PX Admin',
|
|
is_active=True
|
|
).first()
|
|
|
|
elif matching_rule.escalate_to_role == 'ceo':
|
|
# Find CEO for this hospital
|
|
escalation_target = User.objects.filter(
|
|
hospital=complaint.hospital,
|
|
groups__name='CEO',
|
|
is_active=True
|
|
).first()
|
|
|
|
elif matching_rule.escalate_to_role == 'specific_user':
|
|
escalation_target = matching_rule.escalate_to_user
|
|
|
|
if not escalation_target:
|
|
logger.warning(
|
|
f"Could not find escalation target for rule {matching_rule.name} "
|
|
f"({matching_rule.escalate_to_role}) on complaint {complaint_id}"
|
|
)
|
|
return {
|
|
'status': 'no_target_found',
|
|
'rule': matching_rule.name,
|
|
'role': matching_rule.escalate_to_role
|
|
}
|
|
|
|
# Check if already assigned to this person to avoid redundant escalation
|
|
if complaint.assigned_to and complaint.assigned_to.id == escalation_target.id:
|
|
logger.info(
|
|
f"Complaint {complaint_id} already assigned to {escalation_target.get_full_name()}, "
|
|
f"skipping escalation to same person"
|
|
)
|
|
return {
|
|
'status': 'already_assigned',
|
|
'escalated_to': escalation_target.get_full_name()
|
|
}
|
|
|
|
# Perform escalation
|
|
old_assignee = complaint.assigned_to
|
|
complaint.assigned_to = escalation_target
|
|
complaint.escalated_at = timezone.now()
|
|
|
|
# Update metadata with escalation level
|
|
complaint.metadata['escalation_level'] = matching_rule.escalation_level
|
|
complaint.metadata['last_escalation_rule'] = {
|
|
'id': str(matching_rule.id),
|
|
'name': matching_rule.name,
|
|
'level': matching_rule.escalation_level,
|
|
'timestamp': timezone.now().isoformat()
|
|
}
|
|
complaint.save(update_fields=['assigned_to', 'escalated_at', 'metadata'])
|
|
|
|
# Create update
|
|
ComplaintUpdate.objects.create(
|
|
complaint=complaint,
|
|
update_type='escalation',
|
|
message=(
|
|
f"Automatically escalated to {escalation_target.get_full_name()} "
|
|
f"(Level {matching_rule.escalation_level}, Rule: {matching_rule.name}). "
|
|
f"Complaint is {hours_overdue:.1f} hours overdue."
|
|
),
|
|
created_by=None, # System action
|
|
metadata={
|
|
'rule_id': str(matching_rule.id),
|
|
'rule_name': matching_rule.name,
|
|
'escalation_level': matching_rule.escalation_level,
|
|
'hours_overdue': hours_overdue,
|
|
'old_assignee_id': str(old_assignee.id) if old_assignee else None,
|
|
'new_assignee_id': str(escalation_target.id)
|
|
}
|
|
)
|
|
|
|
# Send notifications
|
|
send_complaint_notification.delay(
|
|
complaint_id=str(complaint.id),
|
|
event_type='escalated'
|
|
)
|
|
|
|
# Log audit
|
|
from apps.core.services import create_audit_log
|
|
create_audit_log(
|
|
event_type='complaint_escalated',
|
|
description=f"Complaint automatically escalated to {escalation_target.get_full_name()} (Level {matching_rule.escalation_level})",
|
|
content_object=complaint,
|
|
metadata={
|
|
'rule': matching_rule.name,
|
|
'level': matching_rule.escalation_level,
|
|
'hours_overdue': hours_overdue,
|
|
'escalated_to': escalation_target.get_full_name()
|
|
}
|
|
)
|
|
|
|
logger.info(
|
|
f"Escalated complaint {complaint_id} to {escalation_target.get_full_name()} "
|
|
f"(Level {matching_rule.escalation_level}) using rule '{matching_rule.name}'"
|
|
)
|
|
|
|
return {
|
|
'status': 'escalated',
|
|
'rule': matching_rule.name,
|
|
'level': matching_rule.escalation_level,
|
|
'escalated_to': escalation_target.get_full_name(),
|
|
'hours_overdue': round(hours_overdue, 2)
|
|
}
|
|
|
|
except Complaint.DoesNotExist:
|
|
error_msg = f"Complaint {complaint_id} not found"
|
|
logger.error(error_msg)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
except Exception as e:
|
|
error_msg = f"Error escalating complaint: {str(e)}"
|
|
logger.error(error_msg, exc_info=True)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
|
|
|
|
@shared_task
|
|
def escalate_after_reminder(complaint_id):
|
|
"""
|
|
Escalate complaint after reminder if no action taken.
|
|
|
|
This task is triggered by the SLA reminder task for rules with
|
|
reminder_escalation_enabled. It checks if the complaint has had any
|
|
activity since the reminder was sent, and escalates if not.
|
|
|
|
Args:
|
|
complaint_id: UUID of the Complaint
|
|
|
|
Returns:
|
|
dict: Result with escalation status
|
|
"""
|
|
from apps.complaints.models import Complaint, ComplaintUpdate, EscalationRule
|
|
|
|
try:
|
|
complaint = Complaint.objects.select_related(
|
|
'hospital', 'department', 'assigned_to'
|
|
).get(id=complaint_id)
|
|
|
|
# Check if reminder was sent
|
|
if not complaint.reminder_sent_at:
|
|
logger.info(f"No reminder sent for complaint {complaint_id}, skipping escalation")
|
|
return {'status': 'no_reminder_sent'}
|
|
|
|
# Get SLA config to check reminder-based escalation
|
|
from apps.complaints.models import ComplaintSLAConfig
|
|
try:
|
|
sla_config = ComplaintSLAConfig.objects.get(
|
|
hospital=complaint.hospital,
|
|
severity=complaint.severity,
|
|
priority=complaint.priority,
|
|
is_active=True
|
|
)
|
|
except ComplaintSLAConfig.DoesNotExist:
|
|
logger.info(f"No SLA config for complaint {complaint_id}, skipping reminder escalation")
|
|
return {'status': 'no_sla_config'}
|
|
|
|
# Check if reminder escalation is enabled for this hospital
|
|
rules = EscalationRule.objects.filter(
|
|
hospital=complaint.hospital,
|
|
is_active=True,
|
|
reminder_escalation_enabled=True
|
|
).order_by('escalation_level')
|
|
|
|
# Filter by severity/priority
|
|
if complaint.severity:
|
|
rules = rules.filter(
|
|
Q(severity_filter='') | Q(severity_filter=complaint.severity)
|
|
)
|
|
if complaint.priority:
|
|
rules = rules.filter(
|
|
Q(priority_filter='') | Q(priority_filter=complaint.priority)
|
|
)
|
|
|
|
if not rules.exists():
|
|
logger.info(f"No reminder escalation rules for complaint {complaint_id}")
|
|
return {'status': 'no_rules'}
|
|
|
|
# Get current escalation level
|
|
current_level = complaint.metadata.get('escalation_level', 0)
|
|
|
|
# Find matching rule for next level
|
|
matching_rule = None
|
|
for rule in rules:
|
|
if rule.escalation_level == current_level + 1:
|
|
# Calculate time since reminder
|
|
hours_since_reminder = (timezone.now() - complaint.reminder_sent_at).total_seconds() / 3600
|
|
|
|
# Check if enough time has passed since reminder
|
|
if hours_since_reminder >= rule.reminder_escalation_hours:
|
|
matching_rule = rule
|
|
break
|
|
|
|
if not matching_rule:
|
|
logger.info(
|
|
f"Reminder escalation not yet triggered for complaint {complaint_id} "
|
|
f"(hours since reminder: {(timezone.now() - complaint.reminder_sent_at).total_seconds() / 3600:.1f})"
|
|
)
|
|
return {
|
|
'status': 'not_yet_triggered',
|
|
'hours_since_reminder': (timezone.now() - complaint.reminder_sent_at).total_seconds() / 3600
|
|
}
|
|
|
|
# Trigger the regular escalation task
|
|
result = escalate_complaint_auto.delay(complaint_id)
|
|
|
|
# Add metadata about this being a reminder-based escalation
|
|
if complaint.metadata:
|
|
complaint.metadata['reminder_escalation'] = {
|
|
'rule_id': str(matching_rule.id),
|
|
'rule_name': matching_rule.name,
|
|
'hours_since_reminder': (timezone.now() - complaint.reminder_sent_at).total_seconds() / 3600,
|
|
'timestamp': timezone.now().isoformat()
|
|
}
|
|
complaint.save(update_fields=['metadata'])
|
|
|
|
logger.info(
|
|
f"Reminder-based escalation triggered for complaint {complaint_id} "
|
|
f"using rule '{matching_rule.name}'"
|
|
)
|
|
|
|
return {
|
|
'status': 'reminder_escalation_triggered',
|
|
'rule': matching_rule.name,
|
|
'escalation_result': result
|
|
}
|
|
|
|
except Complaint.DoesNotExist:
|
|
error_msg = f"Complaint {complaint_id} not found"
|
|
logger.error(error_msg)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
except Exception as e:
|
|
error_msg = f"Error in reminder escalation: {str(e)}"
|
|
logger.error(error_msg, exc_info=True)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
|
|
|
|
@shared_task
|
|
def analyze_complaint_with_ai(complaint_id):
|
|
"""
|
|
Analyze a complaint using AI to determine severity and priority and category.
|
|
|
|
This task is triggered when a complaint is created.
|
|
It uses the AI service to analyze the complaint content and classify it.
|
|
|
|
Args:
|
|
complaint_id: UUID of the Complaint
|
|
|
|
Returns:
|
|
dict: Result with severity, priority, category, and reasoning
|
|
"""
|
|
from apps.complaints.models import Complaint
|
|
from apps.core.ai_service import AIService, AIServiceError
|
|
|
|
try:
|
|
complaint = Complaint.objects.select_related('hospital').get(id=complaint_id)
|
|
|
|
logger.info(f"Starting AI analysis for complaint {complaint_id}")
|
|
|
|
# Get category name if category exists
|
|
category_name = None
|
|
if complaint.category:
|
|
category_name = complaint.category.name_en
|
|
|
|
# Analyze complaint using AI service
|
|
try:
|
|
analysis = AIService.analyze_complaint(
|
|
title=complaint.title,
|
|
description=complaint.description,
|
|
category=category_name,
|
|
hospital_id=complaint.hospital.id
|
|
)
|
|
|
|
# Analyze emotion using AI service
|
|
emotion_analysis = AIService.analyze_emotion(
|
|
text=complaint.description
|
|
)
|
|
|
|
# Update complaint with AI-determined values
|
|
old_severity = complaint.severity
|
|
old_priority = complaint.priority
|
|
old_category = complaint.category
|
|
old_department = complaint.department
|
|
|
|
complaint.severity = analysis['severity']
|
|
complaint.priority = analysis['priority']
|
|
|
|
from apps.complaints.models import ComplaintCategory
|
|
if category := ComplaintCategory.objects.filter(name_en=analysis['category']).first():
|
|
complaint.category = category
|
|
|
|
# Update department from AI analysis
|
|
department_name = analysis.get('department', '')
|
|
if department_name:
|
|
from apps.organizations.models import Department
|
|
# Try exact match first (case-insensitive)
|
|
if department := Department.objects.filter(
|
|
hospital_id=complaint.hospital.id,
|
|
name__iexact=department_name,
|
|
status='active'
|
|
).first():
|
|
complaint.department = department
|
|
logger.info(f"Matched department exactly: {department.name}")
|
|
# If no exact match, try partial match
|
|
elif department := Department.objects.filter(
|
|
hospital_id=complaint.hospital.id,
|
|
name__icontains=department_name,
|
|
status='active'
|
|
).first():
|
|
complaint.department = department
|
|
logger.info(f"Matched department partially: {department.name} from '{department_name}'")
|
|
else:
|
|
logger.warning(f"AI suggested department '{department_name}' but no match found in hospital '{complaint.hospital.name}'")
|
|
|
|
# Update title from AI analysis (use English version)
|
|
if analysis.get('title_en'):
|
|
complaint.title = analysis['title_en']
|
|
elif analysis.get('title'):
|
|
complaint.title = analysis['title']
|
|
|
|
# Get ALL staff names from analyze_complaint result (extracted by AI)
|
|
staff_names = analysis.get('staff_names', [])
|
|
primary_staff_name = analysis.get('primary_staff_name', '').strip()
|
|
|
|
# Always get ALL matching staff for PX Admin review
|
|
all_staff_matches = []
|
|
staff_confidence = 0.0
|
|
staff_matching_method = None
|
|
matched_staff_id = None
|
|
|
|
# Capture old staff before matching
|
|
old_staff = complaint.staff
|
|
|
|
# Process ALL extracted staff names
|
|
if staff_names:
|
|
logger.info(f"AI extracted {len(staff_names)} staff name(s): {staff_names}")
|
|
|
|
# Loop through each extracted name and match to database
|
|
for idx, staff_name in enumerate(staff_names):
|
|
staff_name = staff_name.strip()
|
|
if not staff_name:
|
|
continue
|
|
|
|
logger.info(f"Matching staff name {idx+1}/{len(staff_names)}: {staff_name}")
|
|
|
|
# Try matching WITH department filter first (higher confidence if match found)
|
|
matches_for_name, confidence_for_name, method_for_name = match_staff_from_name(
|
|
staff_name=staff_name,
|
|
hospital_id=str(complaint.hospital.id),
|
|
department_name=department_name,
|
|
return_all=True # Return ALL matches
|
|
)
|
|
|
|
# If no match found with department, try WITHOUT department filter
|
|
if not matches_for_name:
|
|
logger.info(f"No match found with department filter '{department_name}' for '{staff_name}', trying without department filter...")
|
|
matches_for_name, confidence_for_name, method_for_name = match_staff_from_name(
|
|
staff_name=staff_name,
|
|
hospital_id=str(complaint.hospital.id),
|
|
department_name=None, # Search all departments
|
|
return_all=True
|
|
)
|
|
|
|
# Add source_name to each match so we know which extracted name it came from
|
|
for match in matches_for_name:
|
|
match['source_name'] = staff_name
|
|
|
|
all_staff_matches.extend(matches_for_name)
|
|
|
|
# Deduplicate matches (same staff can match multiple names)
|
|
seen_ids = set()
|
|
deduped_matches = []
|
|
for match in all_staff_matches:
|
|
if match['id'] not in seen_ids:
|
|
seen_ids.add(match['id'])
|
|
deduped_matches.append(match)
|
|
all_staff_matches = deduped_matches
|
|
|
|
logger.info(f"Total unique staff matches found: {len(all_staff_matches)}")
|
|
|
|
# Logic for staff assignment - CHANGED: NO AUTO-ASSIGNMENT
|
|
needs_staff_review = False
|
|
|
|
if all_staff_matches:
|
|
# Sort by confidence (descending)
|
|
all_staff_matches.sort(key=lambda x: x['confidence'], reverse=True)
|
|
|
|
# Get best match (highest confidence) - BUT DON'T AUTO-ASSIGN
|
|
best_match = all_staff_matches[0]
|
|
matched_staff_id = best_match['id']
|
|
staff_confidence = best_match['confidence']
|
|
staff_matching_method = best_match['matching_method']
|
|
|
|
# DO NOT AUTO-ASSIGN STAFF - Only store suggestions in metadata
|
|
# PX Admins will manually select from suggestions
|
|
logger.info(
|
|
f"Found staff suggestion: {best_match['name_en']} "
|
|
f"for complaint {complaint_id} "
|
|
f"(confidence: {staff_confidence:.2f}, method: {staff_matching_method}) - "
|
|
f"NOT auto-assigned, pending manual review"
|
|
)
|
|
|
|
# Mark for review if:
|
|
# - Low confidence on best match
|
|
# - Multiple names extracted (multiple people mentioned)
|
|
# - Multiple database matches found
|
|
# - ALWAYS mark for review since we're not auto-assigning
|
|
needs_staff_review = True
|
|
|
|
# Assign to department if confidence is high enough (>= 0.7)
|
|
if staff_confidence >= 0.7 and best_match.get('department_id'):
|
|
from apps.organizations.models import Department
|
|
try:
|
|
dept = Department.objects.get(id=best_match['department_id'])
|
|
complaint.department = dept
|
|
logger.info(f"Assigned to department based on staff match: {dept.name}")
|
|
except Department.DoesNotExist:
|
|
pass
|
|
else:
|
|
# No matches found
|
|
logger.warning(f"No staff matches found for extracted names")
|
|
needs_staff_review = False # No review needed if no names found
|
|
else:
|
|
# No staff names extracted
|
|
logger.info("No staff names extracted from complaint")
|
|
needs_staff_review = False
|
|
|
|
# Save reasoning in metadata
|
|
# Use JSON-serializable values instead of model objects
|
|
old_category_name = old_category.name_en if old_category else None
|
|
old_category_id = str(old_category.id) if old_category else None
|
|
old_department_name = old_department.name if old_department else None
|
|
old_department_id = str(old_department.id) if old_department else None
|
|
old_staff_name = f"{old_staff.first_name} {old_staff.last_name}" if old_staff else None
|
|
old_staff_id = str(old_staff.id) if old_staff else None
|
|
|
|
# Initialize metadata if needed
|
|
if not complaint.metadata:
|
|
complaint.metadata = {}
|
|
|
|
# Update or create ai_analysis in metadata with bilingual support and emotion
|
|
complaint.metadata['ai_analysis'] = {
|
|
'title_en': analysis.get('title_en', ''),
|
|
'title_ar': analysis.get('title_ar', ''),
|
|
'short_description_en': analysis.get('short_description_en', ''),
|
|
'short_description_ar': analysis.get('short_description_ar', ''),
|
|
'suggested_action_en': analysis.get('suggested_action_en', ''),
|
|
'suggested_action_ar': analysis.get('suggested_action_ar', ''),
|
|
'reasoning_en': analysis.get('reasoning_en', ''),
|
|
'reasoning_ar': analysis.get('reasoning_ar', ''),
|
|
'emotion': emotion_analysis.get('emotion', 'neutral'),
|
|
'emotion_intensity': emotion_analysis.get('intensity', 0.0),
|
|
'emotion_confidence': emotion_analysis.get('confidence', 0.0),
|
|
'analyzed_at': timezone.now().isoformat(),
|
|
'old_severity': old_severity,
|
|
'old_priority': old_priority,
|
|
'old_category': old_category_name,
|
|
'old_category_id': old_category_id,
|
|
'old_department': old_department_name,
|
|
'old_department_id': old_department_id,
|
|
'old_staff': old_staff_name,
|
|
'old_staff_id': old_staff_id,
|
|
'extracted_staff_names': staff_names,
|
|
'primary_staff_name': primary_staff_name,
|
|
'staff_matches': all_staff_matches,
|
|
'matched_staff_id': matched_staff_id,
|
|
'staff_confidence': staff_confidence,
|
|
'staff_matching_method': staff_matching_method,
|
|
'needs_staff_review': needs_staff_review,
|
|
'staff_match_count': len(all_staff_matches)
|
|
}
|
|
|
|
complaint.save(update_fields=['severity', 'priority', 'category', 'department', 'staff', 'title', 'metadata'])
|
|
|
|
# Re-calculate SLA due date based on new severity
|
|
complaint.due_at = complaint.calculate_sla_due_date()
|
|
complaint.save(update_fields=['due_at'])
|
|
|
|
# Create timeline update for AI completion
|
|
from apps.complaints.models import ComplaintUpdate
|
|
|
|
# Build bilingual message
|
|
emotion_display = emotion_analysis.get('emotion', 'neutral')
|
|
emotion_intensity = emotion_analysis.get('intensity', 0.0)
|
|
|
|
# Build English message
|
|
message_en = f"AI analysis complete: Severity={analysis['severity']}, Priority={analysis['priority']}, Category={analysis.get('category', 'N/A')}, Department={department_name or 'N/A'}"
|
|
if matched_staff_id:
|
|
message_en += f", Staff={f'{complaint.staff.first_name} {complaint.staff.last_name}' if complaint.staff else 'N/A'} (confidence: {staff_confidence:.2f})"
|
|
message_en += f", Emotion={emotion_display} (Intensity: {emotion_intensity:.2f})"
|
|
|
|
# Build Arabic message
|
|
message_ar = f"اكتمل تحليل الذكاء الاصطناعي: الشدة={analysis['severity']}, الأولوية={analysis['priority']}, الفئة={analysis.get('category', 'N/A')}, القسم={department_name or 'N/A'}"
|
|
if matched_staff_id and complaint.staff:
|
|
staff_name_ar = complaint.staff.first_name_ar if complaint.staff.first_name_ar else complaint.staff.first_name
|
|
message_ar += f", الموظف={staff_name_ar} {complaint.staff.last_name_ar if complaint.staff.last_name_ar else complaint.staff.last_name} (الثقة: {staff_confidence:.2f})"
|
|
message_ar += f", العاطفة={emotion_display} (الشدة: {emotion_intensity:.2f})"
|
|
|
|
message = f"{message_en}\n\n{message_ar}"
|
|
|
|
ComplaintUpdate.objects.create(
|
|
complaint=complaint,
|
|
update_type='note',
|
|
message=message
|
|
)
|
|
|
|
# PX Action creation is now MANDATORY for all complaints
|
|
action_id = None
|
|
try:
|
|
logger.info(f"Creating PX Action for complaint {complaint_id} (Mandatory for all complaints)")
|
|
|
|
# Generate PX Action data using AI
|
|
action_data = AIService.create_px_action_from_complaint(complaint)
|
|
|
|
# Create PX Action object
|
|
from apps.px_action_center.models import PXAction, PXActionLog
|
|
from django.contrib.contenttypes.models import ContentType
|
|
|
|
complaint_ct = ContentType.objects.get_for_model(Complaint)
|
|
|
|
action = PXAction.objects.create(
|
|
source_type='complaint',
|
|
content_type=complaint_ct,
|
|
object_id=complaint.id,
|
|
title=action_data['title'],
|
|
description=action_data['description'],
|
|
hospital=complaint.hospital,
|
|
department=complaint.department,
|
|
category=action_data['category'],
|
|
priority=action_data['priority'],
|
|
severity=action_data['severity'],
|
|
status='open',
|
|
metadata={
|
|
'source_complaint_id': str(complaint.id),
|
|
'source_complaint_title': complaint.title,
|
|
'ai_generated': True,
|
|
'auto_created': True,
|
|
'ai_reasoning': action_data.get('reasoning', '')
|
|
}
|
|
)
|
|
|
|
action_id = str(action.id)
|
|
|
|
# Create action log entry
|
|
PXActionLog.objects.create(
|
|
action=action,
|
|
log_type='note',
|
|
message=f"Action automatically generated by AI for complaint: {complaint.title}",
|
|
metadata={
|
|
'complaint_id': str(complaint.id),
|
|
'ai_generated': True,
|
|
'auto_created': True,
|
|
'category': action_data['category'],
|
|
'priority': action_data['priority'],
|
|
'severity': action_data['severity']
|
|
}
|
|
)
|
|
|
|
# Create complaint update
|
|
ComplaintUpdate.objects.create(
|
|
complaint=complaint,
|
|
update_type='note',
|
|
message=f"PX Action automatically created from AI-generated suggestion (Action #{action.id}) - {action_data['category']}",
|
|
metadata={'action_id': str(action.id), 'category': action_data['category']}
|
|
)
|
|
|
|
# Log audit
|
|
from apps.core.services import create_audit_log
|
|
create_audit_log(
|
|
event_type='px_action_auto_created',
|
|
description=f"PX Action automatically created from AI analysis for complaint: {complaint.title}",
|
|
content_object=action,
|
|
metadata={
|
|
'complaint_id': str(complaint.id),
|
|
'category': action_data['category'],
|
|
'priority': action_data['priority'],
|
|
'severity': action_data['severity'],
|
|
'ai_reasoning': action_data.get('reasoning', '')
|
|
}
|
|
)
|
|
|
|
logger.info(f"PX Action {action.id} automatically created for complaint {complaint_id}")
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error auto-creating PX Action for complaint {complaint_id}: {str(e)}", exc_info=True)
|
|
# Don't fail the entire task if PX Action creation fails
|
|
action_id = None
|
|
|
|
logger.info(
|
|
f"AI analysis complete for complaint {complaint_id}: "
|
|
f"severity={old_severity}->{analysis['severity']}, "
|
|
f"priority={old_priority}->{analysis['priority']}, "
|
|
f"category={old_category_name}->{analysis['category']}, "
|
|
f"department={old_department_name}->{department_name}, "
|
|
f"title_en={analysis.get('title_en', '')}"
|
|
)
|
|
|
|
return {
|
|
'status': 'success',
|
|
'complaint_id': str(complaint_id),
|
|
'severity': analysis['severity'],
|
|
'priority': analysis['priority'],
|
|
'category': analysis['category'],
|
|
'department': department_name,
|
|
'title_en': analysis.get('title_en', ''),
|
|
'title_ar': analysis.get('title_ar', ''),
|
|
'short_description_en': analysis.get('short_description_en', ''),
|
|
'short_description_ar': analysis.get('short_description_ar', ''),
|
|
'suggested_action_en': analysis.get('suggested_action_en', ''),
|
|
'suggested_action_ar': analysis.get('suggested_action_ar', ''),
|
|
'reasoning_en': analysis.get('reasoning_en', ''),
|
|
'reasoning_ar': analysis.get('reasoning_ar', ''),
|
|
'emotion': emotion_analysis.get('emotion', 'neutral'),
|
|
'emotion_intensity': emotion_analysis.get('intensity', 0.0),
|
|
'emotion_confidence': emotion_analysis.get('confidence', 0.0),
|
|
'old_severity': old_severity,
|
|
'old_priority': old_priority,
|
|
'px_action_id': action_id,
|
|
'px_action_auto_created': action_id is not None
|
|
}
|
|
|
|
except AIServiceError as e:
|
|
logger.error(f"AI service error for complaint {complaint_id}: {str(e)}")
|
|
# Keep default values (medium/medium) and log the error
|
|
return {
|
|
'status': 'ai_error',
|
|
'complaint_id': str(complaint_id),
|
|
'reason': str(e)
|
|
}
|
|
|
|
except Complaint.DoesNotExist:
|
|
error_msg = f"Complaint {complaint_id} not found"
|
|
logger.error(error_msg)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
|
|
except Exception as e:
|
|
error_msg = f"Error analyzing complaint {complaint_id} with AI: {str(e)}"
|
|
logger.error(error_msg, exc_info=True)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
|
|
|
|
@shared_task
|
|
def send_complaint_notification(complaint_id, event_type):
|
|
"""
|
|
Send notification for complaint events.
|
|
|
|
Args:
|
|
complaint_id: UUID of the Complaint
|
|
event_type: Type of event (created, assigned, overdue, escalated, resolved, closed)
|
|
|
|
Returns:
|
|
dict: Result with notification status
|
|
"""
|
|
from apps.complaints.models import Complaint
|
|
from apps.notifications.services import NotificationService
|
|
|
|
try:
|
|
complaint = Complaint.objects.select_related(
|
|
'hospital', 'patient', 'assigned_to', 'department'
|
|
).get(id=complaint_id)
|
|
|
|
# Determine recipients based on event type
|
|
recipients = []
|
|
|
|
if event_type == 'created':
|
|
# Notify assigned user or department manager
|
|
if complaint.assigned_to:
|
|
recipients.append(complaint.assigned_to)
|
|
elif complaint.department and complaint.department.manager:
|
|
recipients.append(complaint.department.manager)
|
|
|
|
elif event_type == 'assigned':
|
|
# Notify assignee
|
|
if complaint.assigned_to:
|
|
recipients.append(complaint.assigned_to)
|
|
|
|
elif event_type in ['overdue', 'escalated']:
|
|
# Notify assignee and their manager
|
|
if complaint.assigned_to:
|
|
recipients.append(complaint.assigned_to)
|
|
if complaint.department and complaint.department.manager:
|
|
recipients.append(complaint.department.manager)
|
|
|
|
elif event_type == 'resolved':
|
|
# Notify patient
|
|
recipients.append(complaint.patient)
|
|
|
|
elif event_type == 'closed':
|
|
# Notify patient
|
|
recipients.append(complaint.patient)
|
|
|
|
# Send notifications
|
|
notification_count = 0
|
|
for recipient in recipients:
|
|
try:
|
|
# Check if NotificationService has send_notification method
|
|
if hasattr(NotificationService, 'send_notification'):
|
|
NotificationService.send_notification(
|
|
recipient=recipient,
|
|
title=f"Complaint {event_type.title()}: {complaint.title[:50]}",
|
|
message=f"Complaint #{str(complaint.id)[:8]} has been {event_type}.",
|
|
notification_type='complaint',
|
|
related_object=complaint
|
|
)
|
|
notification_count += 1
|
|
else:
|
|
logger.warning(f"NotificationService.send_notification method not available")
|
|
except Exception as e:
|
|
logger.error(f"Failed to send notification to {recipient}: {str(e)}")
|
|
|
|
logger.info(f"Sent {notification_count} notifications for complaint {complaint_id} event: {event_type}")
|
|
|
|
return {
|
|
'status': 'sent',
|
|
'notification_count': notification_count,
|
|
'event_type': event_type
|
|
}
|
|
|
|
except Complaint.DoesNotExist:
|
|
error_msg = f"Complaint {complaint_id} not found"
|
|
logger.error(error_msg)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
except Exception as e:
|
|
error_msg = f"Error sending complaint notification: {str(e)}"
|
|
logger.error(error_msg, exc_info=True)
|
|
return {'status': 'error', 'reason': error_msg}
|
|
|
|
|
|
def get_explanation_sla_config(hospital):
|
|
"""
|
|
Get explanation SLA configuration for a hospital.
|
|
|
|
Returns the first active ExplanationSLAConfig for the hospital.
|
|
Returns None if no config exists (will use defaults).
|
|
"""
|
|
from apps.complaints.models import ExplanationSLAConfig
|
|
|
|
try:
|
|
return ExplanationSLAConfig.objects.get(
|
|
hospital=hospital,
|
|
is_active=True
|
|
)
|
|
except ExplanationSLAConfig.DoesNotExist:
|
|
return None
|
|
|
|
|
|
@shared_task
|
|
def send_explanation_request_email(explanation_id):
|
|
"""
|
|
Send email to staff requesting explanation.
|
|
|
|
Includes link with unique token for staff to submit explanation.
|
|
Sets SLA deadline based on hospital configuration.
|
|
"""
|
|
from apps.complaints.models import ComplaintExplanation
|
|
from django.core.mail import send_mail
|
|
from django.conf import settings
|
|
from django.template.loader import render_to_string
|
|
|
|
explanation = ComplaintExplanation.objects.select_related(
|
|
'complaint', 'staff', 'requested_by'
|
|
).get(id=explanation_id)
|
|
|
|
# Calculate SLA deadline
|
|
sla_config = get_explanation_sla_config(explanation.complaint.hospital)
|
|
sla_hours = sla_config.response_hours if sla_config else 48
|
|
|
|
explanation.sla_due_at = timezone.now() + timezone.timedelta(hours=sla_hours)
|
|
explanation.email_sent_at = timezone.now()
|
|
explanation.save(update_fields=['sla_due_at', 'email_sent_at'])
|
|
|
|
# Prepare email
|
|
context = {
|
|
'explanation': explanation,
|
|
'complaint': explanation.complaint,
|
|
'staff': explanation.staff,
|
|
'requested_by': explanation.requested_by,
|
|
'sla_hours': sla_hours,
|
|
'due_date': explanation.sla_due_at,
|
|
'site_url': settings.SITE_URL if hasattr(settings, 'SITE_URL') else 'http://localhost:8000',
|
|
}
|
|
|
|
subject = f"Explanation Request: Complaint #{str(explanation.complaint.id)[:8]}"
|
|
|
|
# Render email templates
|
|
message_en = render_to_string(
|
|
'complaints/emails/explanation_request_en.txt',
|
|
context
|
|
)
|
|
message_ar = render_to_string(
|
|
'complaints/emails/explanation_request_ar.txt',
|
|
context
|
|
)
|
|
|
|
# Send email
|
|
send_mail(
|
|
subject=subject,
|
|
message=f"{message_en}\n\n{message_ar}",
|
|
from_email=settings.DEFAULT_FROM_EMAIL,
|
|
recipient_list=[explanation.staff.email],
|
|
fail_silently=False
|
|
)
|
|
|
|
# Log audit
|
|
from apps.core.services import create_audit_log
|
|
create_audit_log(
|
|
event_type='explanation_request_sent',
|
|
description=f"Explanation request email sent to {explanation.staff.get_full_name()}",
|
|
content_object=explanation,
|
|
metadata={
|
|
'complaint_id': str(explanation.complaint.id),
|
|
'staff_name': explanation.staff.get_full_name(),
|
|
'sla_hours': sla_hours,
|
|
'due_date': explanation.sla_due_at.isoformat()
|
|
}
|
|
)
|
|
|
|
logger.info(
|
|
f"Explanation request email sent to {explanation.staff.get_full_name()} "
|
|
f"for complaint {explanation.complaint_id}"
|
|
)
|
|
|
|
return {'status': 'sent', 'explanation_id': str(explanation.id)}
|
|
|
|
|
|
@shared_task
|
|
def check_overdue_explanation_requests():
|
|
"""
|
|
Periodic task to check for overdue explanation requests.
|
|
|
|
Runs every 15 minutes (configured in config/celery.py).
|
|
Escalates to staff's manager if explanation not submitted within SLA.
|
|
Follows staff hierarchy via report_to field.
|
|
"""
|
|
from apps.complaints.models import ComplaintExplanation
|
|
from apps.organizations.models import Staff
|
|
|
|
now = timezone.now()
|
|
|
|
# Get explanation requests that are:
|
|
# - Not submitted (is_used=False)
|
|
# - Email sent (email_sent_at is not null)
|
|
# - Past SLA deadline
|
|
overdue_explanations = ComplaintExplanation.objects.filter(
|
|
is_used=False,
|
|
email_sent_at__isnull=False,
|
|
sla_due_at__lt=now,
|
|
escalated_to_manager__isnull=True # Not yet escalated
|
|
).select_related('complaint', 'staff', 'staff__department')
|
|
|
|
escalated_count = 0
|
|
|
|
for explanation in overdue_explanations:
|
|
# Mark as overdue
|
|
if not explanation.is_overdue:
|
|
explanation.is_overdue = True
|
|
explanation.save(update_fields=['is_overdue'])
|
|
|
|
# Get SLA config
|
|
sla_config = get_explanation_sla_config(explanation.complaint.hospital)
|
|
|
|
# Check if auto-escalation is enabled
|
|
if not sla_config or not sla_config.auto_escalate_enabled:
|
|
logger.info(
|
|
f"Auto-escalation disabled for explanation {explanation.id}, "
|
|
f"hospital {explanation.complaint.hospital.name}"
|
|
)
|
|
continue
|
|
|
|
# Get current escalation level
|
|
current_level = explanation.metadata.get('escalation_level', 0)
|
|
|
|
# Check max escalation level
|
|
max_level = sla_config.max_escalation_levels if sla_config else 3
|
|
|
|
if current_level >= max_level:
|
|
logger.info(f"Explanation {explanation.id} reached max escalation level {max_level}")
|
|
continue
|
|
|
|
# Calculate hours overdue
|
|
hours_overdue = (now - explanation.sla_due_at).total_seconds() / 3600
|
|
|
|
# Check if we should escalate now
|
|
escalation_delay = sla_config.escalation_hours_overdue if sla_config else 0
|
|
if hours_overdue < escalation_delay:
|
|
logger.info(
|
|
f"Explanation {explanation.id} overdue by {hours_overdue:.1f}h, "
|
|
f"waiting for escalation delay of {escalation_delay}h"
|
|
)
|
|
continue
|
|
|
|
# Determine escalation target using staff hierarchy
|
|
escalation_target = None
|
|
|
|
if explanation.staff and explanation.staff.report_to:
|
|
# Escalate to staff's manager
|
|
escalation_target = explanation.staff.report_to
|
|
|
|
# Check if manager already has an explanation request for this complaint
|
|
existing_explanation = ComplaintExplanation.objects.filter(
|
|
complaint=explanation.complaint,
|
|
staff=escalation_target
|
|
).first()
|
|
|
|
if existing_explanation:
|
|
logger.info(
|
|
f"Staff {escalation_target.get_full_name()} already has an explanation "
|
|
f"request for complaint {explanation.complaint.id}, skipping escalation"
|
|
)
|
|
# Mark as escalated anyway to avoid repeated checks
|
|
explanation.escalated_to_manager = existing_explanation
|
|
explanation.escalated_at = now
|
|
explanation.metadata['escalation_level'] = current_level + 1
|
|
explanation.save(update_fields=['escalated_to_manager', 'escalated_at', 'metadata'])
|
|
escalated_count += 1
|
|
continue
|
|
|
|
# Create new explanation request for manager
|
|
new_explanation = ComplaintExplanation.objects.create(
|
|
complaint=explanation.complaint,
|
|
staff=escalation_target,
|
|
explanation='', # Will be filled by manager
|
|
requested_by=explanation.requested_by,
|
|
request_message=(
|
|
f"Escalated from {explanation.staff.get_full_name()}. "
|
|
f"Staff member did not provide explanation within SLA. "
|
|
f"Please provide your explanation about this complaint."
|
|
),
|
|
submitted_via='email_link',
|
|
metadata={
|
|
'escalated_from_explanation_id': str(explanation.id),
|
|
'escalation_level': current_level + 1,
|
|
'original_staff_id': str(explanation.staff.id),
|
|
'original_staff_name': explanation.staff.get_full_name()
|
|
}
|
|
)
|
|
|
|
# Link old explanation to new one
|
|
explanation.escalated_to_manager = new_explanation
|
|
explanation.escalated_at = now
|
|
explanation.metadata['escalation_level'] = current_level + 1
|
|
explanation.save(update_fields=['escalated_to_manager', 'escalated_at', 'metadata'])
|
|
|
|
# Send email to manager
|
|
send_explanation_request_email.delay(str(new_explanation.id))
|
|
|
|
escalated_count += 1
|
|
|
|
logger.info(
|
|
f"Escalated explanation request {explanation.id} to manager "
|
|
f"{escalation_target.get_full_name()} (Level {current_level + 1})"
|
|
)
|
|
else:
|
|
logger.warning(
|
|
f"No escalation target for explanation {explanation.id} "
|
|
f"(staff has no report_to manager)"
|
|
)
|
|
|
|
return {
|
|
'overdue_count': overdue_explanations.count(),
|
|
'escalated_count': escalated_count
|
|
}
|
|
|
|
|
|
@shared_task
|
|
def send_explanation_reminders():
|
|
"""
|
|
Send reminder emails for explanation requests approaching deadline.
|
|
|
|
Runs every hour via Celery Beat.
|
|
Sends reminder to staff if explanation not submitted and deadline approaching.
|
|
"""
|
|
from apps.complaints.models import ComplaintExplanation
|
|
from django.core.mail import send_mail
|
|
from django.conf import settings
|
|
from django.template.loader import render_to_string
|
|
|
|
now = timezone.now()
|
|
|
|
# Get explanation requests that:
|
|
# - Not submitted (is_used=False)
|
|
# - Email sent (email_sent_at is not null)
|
|
# - Haven't been reminded yet
|
|
# - Approaching deadline
|
|
explanations = ComplaintExplanation.objects.filter(
|
|
is_used=False,
|
|
email_sent_at__isnull=False,
|
|
reminder_sent_at__isnull=True,
|
|
escalated_to_manager__isnull=True
|
|
).select_related('complaint', 'staff')
|
|
|
|
reminder_count = 0
|
|
|
|
for explanation in explanations:
|
|
# Get SLA config
|
|
sla_config = get_explanation_sla_config(explanation.complaint.hospital)
|
|
reminder_hours_before = sla_config.reminder_hours_before if sla_config else 12
|
|
|
|
# Calculate reminder threshold time
|
|
reminder_time = explanation.sla_due_at - timezone.timedelta(hours=reminder_hours_before)
|
|
|
|
# Check if we should send reminder now
|
|
if now >= reminder_time:
|
|
# Calculate hours remaining
|
|
hours_remaining = (explanation.sla_due_at - now).total_seconds() / 3600
|
|
|
|
if hours_remaining < 0:
|
|
continue # Already overdue, will be handled by check_overdue_explanation_requests
|
|
|
|
# Prepare email context
|
|
context = {
|
|
'explanation': explanation,
|
|
'complaint': explanation.complaint,
|
|
'staff': explanation.staff,
|
|
'hours_remaining': int(hours_remaining),
|
|
'due_date': explanation.sla_due_at,
|
|
'site_url': settings.SITE_URL if hasattr(settings, 'SITE_URL') else 'http://localhost:8000',
|
|
}
|
|
|
|
subject = f"Reminder: Explanation Request - Complaint #{str(explanation.complaint.id)[:8]}"
|
|
|
|
try:
|
|
# Render email templates
|
|
message_en = render_to_string(
|
|
'complaints/emails/explanation_reminder_en.txt',
|
|
context
|
|
)
|
|
message_ar = render_to_string(
|
|
'complaints/emails/explanation_reminder_ar.txt',
|
|
context
|
|
)
|
|
|
|
# Send email
|
|
send_mail(
|
|
subject=subject,
|
|
message=f"{message_en}\n\n{message_ar}",
|
|
from_email=settings.DEFAULT_FROM_EMAIL,
|
|
recipient_list=[explanation.staff.email],
|
|
fail_silently=False
|
|
)
|
|
|
|
# Update explanation
|
|
explanation.reminder_sent_at = now
|
|
explanation.save(update_fields=['reminder_sent_at'])
|
|
|
|
reminder_count += 1
|
|
|
|
logger.info(
|
|
f"Explanation reminder sent to {explanation.staff.get_full_name()} "
|
|
f"for complaint {explanation.complaint_id} "
|
|
f"({int(hours_remaining)} hours remaining)"
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(f"Failed to send explanation reminder for {explanation.id}: {str(e)}")
|
|
|
|
return {
|
|
'status': 'completed',
|
|
'reminders_sent': reminder_count
|
|
}
|
|
|
|
|
|
@shared_task
|
|
def send_sla_reminders():
|
|
"""
|
|
Send SLA reminder emails for complaints approaching deadline.
|
|
|
|
Runs every hour via Celery Beat.
|
|
Finds complaints where reminder should be sent based on hospital's SLA configuration.
|
|
Sends reminder email to assigned user or department manager.
|
|
Creates timeline entry for reminder sent.
|
|
|
|
Returns:
|
|
dict: Result with reminder count and details
|
|
"""
|
|
from apps.complaints.models import Complaint, ComplaintUpdate, ComplaintStatus, ComplaintSLAConfig
|
|
from apps.notifications.services import NotificationService
|
|
from django.core.mail import send_mail
|
|
from django.conf import settings
|
|
from django.template.loader import render_to_string
|
|
|
|
try:
|
|
now = timezone.now()
|
|
|
|
# Get active complaints that haven't been reminded yet OR need second reminder
|
|
active_complaints = Complaint.objects.filter(
|
|
status__in=[ComplaintStatus.OPEN, ComplaintStatus.IN_PROGRESS]
|
|
).filter(
|
|
models.Q(reminder_sent_at__isnull=True) | # First reminder not sent
|
|
models.Q(
|
|
reminder_sent_at__isnull=False,
|
|
second_reminder_sent_at__isnull=True,
|
|
reminder_sent_at__lt=now - timezone.timedelta(hours=1) # At least 1 hour after first reminder
|
|
)
|
|
).select_related('hospital', 'patient', 'assigned_to', 'department', 'category')
|
|
|
|
reminder_count = 0
|
|
skipped_count = 0
|
|
|
|
for complaint in active_complaints:
|
|
# Get SLA config for this complaint
|
|
try:
|
|
sla_config = ComplaintSLAConfig.objects.get(
|
|
hospital=complaint.hospital,
|
|
severity=complaint.severity,
|
|
priority=complaint.priority,
|
|
is_active=True
|
|
)
|
|
reminder_hours_before = sla_config.reminder_hours_before
|
|
except ComplaintSLAConfig.DoesNotExist:
|
|
# Use default of 24 hours
|
|
reminder_hours_before = 24
|
|
|
|
# Calculate reminder threshold time
|
|
reminder_time = complaint.due_at - timezone.timedelta(hours=reminder_hours_before)
|
|
|
|
# Check if we should send FIRST reminder now
|
|
if now >= reminder_time and complaint.reminder_sent_at is None:
|
|
# Determine recipient
|
|
recipient = complaint.assigned_to
|
|
if not recipient and complaint.department and complaint.department.manager:
|
|
recipient = complaint.department.manager
|
|
|
|
if not recipient:
|
|
logger.warning(
|
|
f"No recipient for SLA reminder on complaint {complaint.id} "
|
|
f"(no assigned user or department manager)"
|
|
)
|
|
skipped_count += 1
|
|
continue
|
|
|
|
# Calculate hours remaining
|
|
hours_remaining = (complaint.due_at - now).total_seconds() / 3600
|
|
|
|
# Prepare email context
|
|
context = {
|
|
'complaint': complaint,
|
|
'recipient': recipient,
|
|
'hours_remaining': int(hours_remaining),
|
|
'due_date': complaint.due_at,
|
|
'site_url': f"{settings.SITE_URL if hasattr(settings, 'SITE_URL') else 'http://localhost:8000'}",
|
|
}
|
|
|
|
# Render email templates
|
|
subject = f"SLA Reminder: Complaint #{str(complaint.id)[:8]} - {complaint.title[:50]}"
|
|
|
|
try:
|
|
# Try to send via NotificationService first
|
|
if hasattr(NotificationService, 'send_notification'):
|
|
NotificationService.send_notification(
|
|
recipient=recipient,
|
|
title=subject,
|
|
message=(
|
|
f"This is a reminder that complaint #{str(complaint.id)[:8]} "
|
|
f"is due in {int(hours_remaining)} hours. "
|
|
f"Please take action to avoid SLA breach."
|
|
),
|
|
notification_type='complaint',
|
|
related_object=complaint,
|
|
metadata={'event_type': 'sla_reminder'}
|
|
)
|
|
else:
|
|
# Fallback to direct email
|
|
message_en = render_to_string(
|
|
'complaints/emails/sla_reminder_en.txt',
|
|
context
|
|
)
|
|
message_ar = render_to_string(
|
|
'complaints/emails/sla_reminder_ar.txt',
|
|
context
|
|
)
|
|
|
|
# Send to recipient's email
|
|
recipient_email = recipient.email if hasattr(recipient, 'email') else None
|
|
if recipient_email:
|
|
send_mail(
|
|
subject=subject,
|
|
message=f"{message_en}\n\n{message_ar}",
|
|
from_email=settings.DEFAULT_FROM_EMAIL,
|
|
recipient_list=[recipient_email],
|
|
fail_silently=False
|
|
)
|
|
else:
|
|
logger.warning(f"No email for recipient {recipient}")
|
|
skipped_count += 1
|
|
continue
|
|
|
|
# Update complaint
|
|
complaint.reminder_sent_at = now
|
|
complaint.save(update_fields=['reminder_sent_at'])
|
|
|
|
# Create timeline entry
|
|
ComplaintUpdate.objects.create(
|
|
complaint=complaint,
|
|
update_type='note',
|
|
message=(
|
|
f"SLA reminder sent to {recipient.get_full_name()}. "
|
|
f"Complaint is due in {int(hours_remaining)} hours."
|
|
),
|
|
created_by=None, # System action
|
|
metadata={
|
|
'event_type': 'sla_reminder',
|
|
'hours_remaining': int(hours_remaining),
|
|
'recipient_id': str(recipient.id)
|
|
}
|
|
)
|
|
|
|
# Log audit
|
|
from apps.core.services import create_audit_log
|
|
create_audit_log(
|
|
event_type='sla_reminder_sent',
|
|
description=f"SLA reminder sent for complaint {complaint.id}",
|
|
content_object=complaint,
|
|
metadata={
|
|
'recipient': recipient.get_full_name(),
|
|
'hours_remaining': int(hours_remaining)
|
|
}
|
|
)
|
|
|
|
reminder_count += 1
|
|
logger.info(
|
|
f"SLA reminder sent for complaint {complaint.id} "
|
|
f"to {recipient.get_full_name()} "
|
|
f"({int(hours_remaining)} hours remaining)"
|
|
)
|
|
|
|
# Trigger reminder-based escalation check
|
|
escalate_after_reminder.delay(str(complaint.id))
|
|
|
|
except Exception as e:
|
|
logger.error(f"Failed to send SLA reminder for complaint {complaint.id}: {str(e)}")
|
|
skipped_count += 1
|
|
|
|
# Check if we should send SECOND reminder now
|
|
elif (sla_config.second_reminder_enabled and
|
|
complaint.reminder_sent_at is not None and
|
|
complaint.second_reminder_sent_at is None):
|
|
|
|
# Calculate second reminder threshold time
|
|
second_reminder_hours_before = sla_config.second_reminder_hours_before
|
|
second_reminder_time = complaint.due_at - timezone.timedelta(hours=second_reminder_hours_before)
|
|
|
|
if now >= second_reminder_time:
|
|
# Determine recipient
|
|
recipient = complaint.assigned_to
|
|
if not recipient and complaint.department and complaint.department.manager:
|
|
recipient = complaint.department.manager
|
|
|
|
if not recipient:
|
|
logger.warning(
|
|
f"No recipient for second SLA reminder on complaint {complaint.id} "
|
|
f"(no assigned user or department manager)"
|
|
)
|
|
skipped_count += 1
|
|
continue
|
|
|
|
# Calculate hours remaining
|
|
hours_remaining = (complaint.due_at - now).total_seconds() / 3600
|
|
|
|
# Prepare email context
|
|
context = {
|
|
'complaint': complaint,
|
|
'recipient': recipient,
|
|
'hours_remaining': int(hours_remaining),
|
|
'due_date': complaint.due_at,
|
|
'site_url': f"{settings.SITE_URL if hasattr(settings, 'SITE_URL') else 'http://localhost:8000'}",
|
|
}
|
|
|
|
# Render email templates
|
|
subject = f"URGENT - Second SLA Reminder: Complaint #{str(complaint.id)[:8]} - {complaint.title[:50]}"
|
|
|
|
try:
|
|
# Try to send via NotificationService first
|
|
if hasattr(NotificationService, 'send_notification'):
|
|
NotificationService.send_notification(
|
|
recipient=recipient,
|
|
title=subject,
|
|
message=(
|
|
f"This is the SECOND and FINAL reminder that complaint #{str(complaint.id)[:8]} "
|
|
f"is due in {int(hours_remaining)} hours. "
|
|
f"URGENT action required to avoid SLA breach and escalation."
|
|
),
|
|
notification_type='complaint',
|
|
related_object=complaint,
|
|
metadata={'event_type': 'sla_second_reminder'}
|
|
)
|
|
else:
|
|
# Fallback to direct email
|
|
message_en = render_to_string(
|
|
'complaints/emails/sla_second_reminder_en.txt',
|
|
context
|
|
)
|
|
message_ar = render_to_string(
|
|
'complaints/emails/sla_second_reminder_ar.txt',
|
|
context
|
|
)
|
|
|
|
# Send to recipient's email
|
|
recipient_email = recipient.email if hasattr(recipient, 'email') else None
|
|
if recipient_email:
|
|
send_mail(
|
|
subject=subject,
|
|
message=f"{message_en}\n\n{message_ar}",
|
|
from_email=settings.DEFAULT_FROM_EMAIL,
|
|
recipient_list=[recipient_email],
|
|
fail_silently=False
|
|
)
|
|
else:
|
|
logger.warning(f"No email for recipient {recipient}")
|
|
skipped_count += 1
|
|
continue
|
|
|
|
# Update complaint
|
|
complaint.second_reminder_sent_at = now
|
|
complaint.save(update_fields=['second_reminder_sent_at'])
|
|
|
|
# Create timeline entry
|
|
ComplaintUpdate.objects.create(
|
|
complaint=complaint,
|
|
update_type='note',
|
|
message=(
|
|
f"SECOND SLA reminder sent to {recipient.get_full_name()}. "
|
|
f"Complaint is due in {int(hours_remaining)} hours. "
|
|
f"This is the final reminder before escalation."
|
|
),
|
|
created_by=None, # System action
|
|
metadata={
|
|
'event_type': 'sla_second_reminder',
|
|
'hours_remaining': int(hours_remaining),
|
|
'recipient_id': str(recipient.id)
|
|
}
|
|
)
|
|
|
|
# Log audit
|
|
from apps.core.services import create_audit_log
|
|
create_audit_log(
|
|
event_type='sla_second_reminder_sent',
|
|
description=f"Second SLA reminder sent for complaint {complaint.id}",
|
|
content_object=complaint,
|
|
metadata={
|
|
'recipient': recipient.get_full_name(),
|
|
'hours_remaining': int(hours_remaining)
|
|
}
|
|
)
|
|
|
|
reminder_count += 1
|
|
logger.info(
|
|
f"Second SLA reminder sent for complaint {complaint.id} "
|
|
f"to {recipient.get_full_name()} "
|
|
f"({int(hours_remaining)} hours remaining)"
|
|
)
|
|
|
|
# Trigger reminder-based escalation check (more urgent now)
|
|
escalate_after_reminder.delay(str(complaint.id))
|
|
|
|
except Exception as e:
|
|
logger.error(f"Failed to send second SLA reminder for complaint {complaint.id}: {str(e)}")
|
|
skipped_count += 1
|
|
|
|
logger.info(
|
|
f"SLA reminder check complete: {reminder_count} sent, {skipped_count} skipped"
|
|
)
|
|
|
|
return {
|
|
'status': 'completed',
|
|
'reminders_sent': reminder_count,
|
|
'skipped': skipped_count
|
|
}
|
|
|
|
except Exception as e:
|
|
error_msg = f"Error in SLA reminder task: {str(e)}"
|
|
logger.error(error_msg, exc_info=True)
|
|
return {'status': 'error', 'reason': error_msg}
|