# response_formatter.py from typing import Dict, List, Any class ResponseFormatter: @staticmethod def format_healthcare_response(scenario_text: str, analysis_results: Dict[str, Any]) -> str: """Format healthcare analysis response with detailed structure""" response = "# Healthcare Scenario Analysis\n\n" # Executive Summary response += "## Executive Summary\n\n" response += ResponseFormatter._generate_executive_summary(analysis_results) response += "\n\n" # Data Preparation response += "## 1. Data Preparation\n\n" response += ResponseFormatter._generate_data_section(analysis_results) response += "\n\n" # Analysis Sections if "facility_distribution" in analysis_results: response += "## 2. Facility Distribution Analysis\n\n" response += ResponseFormatter._format_facility_distribution(analysis_results["facility_distribution"]) response += "\n\n" if "capacity_analysis" in analysis_results: response += "## 3. Capacity Analysis\n\n" response += ResponseFormatter._format_capacity_analysis(analysis_results["capacity_analysis"]) response += "\n\n" if "resource_allocation" in analysis_results: response += "## 4. Resource Allocation Analysis\n\n" response += ResponseFormatter._format_resource_allocation(analysis_results["resource_allocation"]) response += "\n\n" if "trends" in analysis_results: response += "## 5. Trend Analysis\n\n" response += ResponseFormatter._format_trends(analysis_results["trends"]) response += "\n\n" # Recommendations if "recommendations" in analysis_results: response += "## 6. Operational Recommendations\n\n" response += ResponseFormatter._format_recommendations(analysis_results["recommendations"]) response += "\n\n" # Future Integration if "future_integration" in analysis_results: response += "## 7. Future Integration Opportunities\n\n" response += ResponseFormatter._format_integration_opportunities(analysis_results["future_integration"]) response += "\n\n" # Provenance response += "## 8. Provenance\n\n" response += "This analysis is based on:\n" response += "- Scenario description provided by the user\n" response += "- Uploaded data files\n" response += "- Calculations performed on the provided data\n" return response @staticmethod def _generate_executive_summary(results: Dict[str, Any]) -> str: """Generate executive summary based on analysis results""" summary = [] if "capacity_analysis" in results: capacity = results["capacity_analysis"] if "total_capacity" in capacity: summary.append(f"Total system capacity: {capacity['total_capacity']:,} beds") if "average_utilization" in capacity: summary.append(f"Average utilization: {capacity['average_utilization']:.1%}") if "facility_distribution" in results: dist = results["facility_distribution"] if "geographic_inequality" in dist: inequality = dist["geographic_inequality"] level = "High" if inequality > 0.4 else "Moderate" if inequality > 0.2 else "Low" summary.append(f"Geographic distribution inequality: {level} (Gini: {inequality:.2f})") if "recommendations" in results: high_priority = [r for r in results["recommendations"] if r.get("priority") == "High"] if high_priority: summary.append(f"{len(high_priority)} high-priority recommendations identified") return " | ".join(summary) if summary else "No key metrics identified" @staticmethod def _generate_data_section(results: Dict[str, Any]) -> str: """Generate data preparation section""" data_sources = [] if "facility_distribution" in results: data_sources.append("Facility registry data") if "capacity_analysis" in results: data_sources.append("Bed capacity and utilization data") if "resource_allocation" in results: data_sources.append("Resource allocation data") if "trends" in results: data_sources.append("Historical trend data") if not data_sources: return "No relevant data sources identified" response = "The following data sources were used in this analysis:\n\n" for source in data_sources: response += f"- {source}\n" response += "\nData quality checks and transformations were applied to ensure accuracy and consistency." return response @staticmethod def _format_facility_distribution(dist_results: Dict[str, Any]) -> str: """Format facility distribution analysis results""" response = "" if "geographic_distribution" in dist_results: response += "### Geographic Distribution\n\n" response += "| Region | Facility Count |\n" response += "|--------|---------------|\n" for region, count in dist_results["geographic_distribution"].items(): response += f"| {region} | {count} |\n" response += "\n" if "geographic_inequality" in dist_results: inequality = dist_results["geographic_inequality"] level = "High" if inequality > 0.4 else "Moderate" if inequality > 0.2 else "Low" response += f"**Geographic Inequality**: {level} (Gini coefficient: {inequality:.2f})\n\n" if "facility_type_distribution" in dist_results: response += "### Facility Type Distribution\n\n" response += "| Facility Type | Count |\n" response += "|---------------|-------|\n" for ftype, count in dist_results["facility_type_distribution"].items(): response += f"| {ftype} | {count} |\n" response += "\n" if "facility_diversity" in dist_results: diversity = dist_results["facility_diversity"] response += f"**Facility Diversity Index**: {diversity:.2f} (higher values indicate more diversity)\n\n" return response if response else "No facility distribution data available" @staticmethod def _format_capacity_analysis(capacity_results: Dict[str, Any]) -> str: """Format capacity analysis results""" response = "" if "total_capacity" in capacity_results: response += f"**Total System Capacity**: {capacity_results['total_capacity']:,} beds\n\n" if "capacity_by_type" in capacity_results: response += "### Capacity by Facility Type\n\n" response += "| Facility Type | Capacity |\n" response += "|---------------|----------|\n" for ftype, capacity in capacity_results["capacity_by_type"].items(): response += f"| {ftype} | {capacity:,} |\n" response += "\n" if "average_utilization" in capacity_results: response += f"**Average System Utilization**: {capacity_results['average_utilization']:.1%}\n\n" if "utilization_by_type" in capacity_results: response += "### Utilization by Facility Type\n\n" response += "| Facility Type | Utilization |\n" response += "|---------------|-------------|\n" for ftype, util in capacity_results["utilization_by_type"].items(): response += f"| {ftype} | {util:.1%} |\n" response += "\n" if "capacity_trends" in capacity_results: response += "### Capacity Trends\n\n" response += "| Year | Capacity |\n" response += "|------|----------|\n" for year, capacity in capacity_results["capacity_trends"].items(): response += f"| {year} | {capacity:,} |\n" response += "\n" if "capacity_growth_rate" in capacity_results: growth = capacity_results["capacity_growth_rate"] response += f"**Overall Growth Rate**: {growth:.1f}%\n\n" return response if response else "No capacity data available" @staticmethod def _format_resource_allocation(resource_results: Dict[str, Any]) -> str: """Format resource allocation results""" response = "" if "total_staff" in resource_results: response += f"**Total Staff**: {resource_results['total_staff']:,} FTEs\n\n" if "staff_per_bed_ratio" in resource_results: ratio = resource_results["staff_per_bed_ratio"] response += f"**Staff per Bed Ratio**: {ratio:.2f}\n\n" if ratio < 1.5: response += "⚠️ This ratio is below recommended levels\n\n" if "equipment_summary" in resource_results: response += "### Equipment Summary\n\n" for equipment, count in resource_results["equipment_summary"].items(): response += f"- {equipment}: {count:,}\n" response += "\n" return response if response else "No resource allocation data available" @staticmethod def _format_trends(trend_results: Dict[str, Any]) -> str: """Format trend analysis results""" response = "" if "year_over_year_trends" in trend_results: response += "### Year-over-Year Changes\n\n" response += "| Period | Absolute Change | Percentage Change |\n" response += "|--------|-----------------|-------------------|\n" for period, change in trend_results["year_over_year_trends"].items(): abs_change = change["absolute_change"] pct_change = change["percentage_change"] response += f"| {period} | {abs_change:+,} | {pct_change:+.1f}% |\n" response += "\n" return response if response else "No trend data available" @staticmethod def _format_recommendations(recommendations: List[Dict[str, str]]) -> str: """Format operational recommendations""" if not recommendations: return "No specific recommendations generated" response = "" for i, rec in enumerate(recommendations, 1): response += f"### {i}. {rec['title']}\n\n" response += f"**Priority**: {rec.get('priority', 'Medium')}\n\n" response += f"{rec['description']}\n\n" response += f"*Data source: {rec.get('data_source', 'Analysis results')}*\n\n" return response @staticmethod def _format_integration_opportunities(opportunities: Dict[str, Any]) -> str: """Format future integration opportunities""" response = "" if "data_integration" in opportunities: response += "### Data Integration Opportunities\n\n" for opp in opportunities["data_integration"]: response += f"**{opp['opportunity']}**\n\n" response += f"{opp['description']}\n\n" response += f"*Expected benefit: {opp['benefit']}*\n\n" if "ai_applications" in opportunities: response += "### AI Application Opportunities\n\n" for opp in opportunities["ai_applications"]: response += f"**{opp['opportunity']}**\n\n" response += f"{opp['description']}\n\n" response += f"*Expected benefit: {opp['benefit']}*\n\n" if "enhanced_metrics" in opportunities: response += "### Enhanced Metrics\n\n" for metric in opportunities["enhanced_metrics"]: response += f"**{metric['metric']}**\n\n" response += f"{metric['description']}\n\n" response += f"*Expected benefit: {metric['benefit']}*\n\n" return response if response else "No integration opportunities identified"