feat: Add Streamlit dashboard with Blueprint compliance (v2.1.0)
Dashboard Features: - 8 navigation sections: Overview, Outcomes, Poor CX, FCR, Churn, Agent, Call Explorer, Export - Beyond Brand Identity styling (colors #6D84E3, Outfit font) - RCA Sankey diagram (Driver → Outcome → Churn Risk flow) - Correlation heatmaps (driver co-occurrence, driver-outcome) - Outcome Deep Dive (root causes, correlation, duration analysis) - Export functionality (Excel, HTML, JSON) Blueprint Compliance: - FCR: 4 categories (Primera Llamada/Rellamada × Sin/Con Riesgo de Fuga) - Churn: Binary view (Sin Riesgo de Fuga / En Riesgo de Fuga) - Agent: Talento Para Replicar / Oportunidades de Mejora - Fixed FCR rate calculation (only FIRST_CALL counts as success) Technical: - Streamlit + Plotly for interactive visualizations - Light theme configuration (.streamlit/config.toml) - Fixed Plotly colorbar titlefont deprecation Documentation: - Updated PROJECT_CONTEXT.md, TODO.md, CHANGELOG.md - Added 4 new technical decisions (TD-014 to TD-017) - Created TROUBLESHOOTING.md with 10 common issues Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
sujucu70
268
src/exports/excel_export.py
Normal file
268
src/exports/excel_export.py
Normal file
@@ -0,0 +1,268 @@
|
||||
"""
|
||||
CXInsights - Excel Export
|
||||
|
||||
Exports analysis results to Excel format with multiple sheets.
|
||||
"""
|
||||
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
from src.aggregation.models import BatchAggregation
|
||||
from src.models.call_analysis import CallAnalysis
|
||||
|
||||
# Try to import openpyxl, provide fallback
|
||||
try:
|
||||
from openpyxl import Workbook
|
||||
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
|
||||
from openpyxl.utils import get_column_letter
|
||||
OPENPYXL_AVAILABLE = True
|
||||
except ImportError:
|
||||
OPENPYXL_AVAILABLE = False
|
||||
|
||||
|
||||
def export_to_excel(
|
||||
batch_id: str,
|
||||
aggregation: BatchAggregation,
|
||||
analyses: list[CallAnalysis],
|
||||
output_dir: Path,
|
||||
) -> Path:
|
||||
"""
|
||||
Export results to Excel file.
|
||||
|
||||
Creates workbook with sheets:
|
||||
- Summary: High-level metrics
|
||||
- Lost Sales Drivers: Driver frequencies and severity
|
||||
- Poor CX Drivers: Driver frequencies and severity
|
||||
- Call Details: Individual call results
|
||||
- Emergent Patterns: New patterns found
|
||||
|
||||
Args:
|
||||
batch_id: Batch identifier
|
||||
aggregation: Aggregation results
|
||||
analyses: Individual call analyses
|
||||
output_dir: Output directory
|
||||
|
||||
Returns:
|
||||
Path to Excel file
|
||||
"""
|
||||
if not OPENPYXL_AVAILABLE:
|
||||
raise ImportError(
|
||||
"openpyxl is required for Excel export. "
|
||||
"Install with: pip install openpyxl"
|
||||
)
|
||||
|
||||
output_dir = Path(output_dir)
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
wb = Workbook()
|
||||
|
||||
# Style definitions
|
||||
header_font = Font(bold=True, color="FFFFFF")
|
||||
header_fill = PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid")
|
||||
header_alignment = Alignment(horizontal="center", vertical="center")
|
||||
|
||||
# Sheet 1: Summary
|
||||
ws_summary = wb.active
|
||||
ws_summary.title = "Summary"
|
||||
_create_summary_sheet(ws_summary, batch_id, aggregation, analyses, header_font, header_fill)
|
||||
|
||||
# Sheet 2: Lost Sales Drivers
|
||||
ws_lost_sales = wb.create_sheet("Lost Sales Drivers")
|
||||
_create_drivers_sheet(
|
||||
ws_lost_sales,
|
||||
aggregation.lost_sales_frequencies,
|
||||
aggregation.lost_sales_severities,
|
||||
header_font,
|
||||
header_fill,
|
||||
)
|
||||
|
||||
# Sheet 3: Poor CX Drivers
|
||||
ws_poor_cx = wb.create_sheet("Poor CX Drivers")
|
||||
_create_drivers_sheet(
|
||||
ws_poor_cx,
|
||||
aggregation.poor_cx_frequencies,
|
||||
aggregation.poor_cx_severities,
|
||||
header_font,
|
||||
header_fill,
|
||||
)
|
||||
|
||||
# Sheet 4: Call Details
|
||||
ws_calls = wb.create_sheet("Call Details")
|
||||
_create_calls_sheet(ws_calls, analyses, header_font, header_fill)
|
||||
|
||||
# Sheet 5: Emergent Patterns
|
||||
if aggregation.emergent_patterns:
|
||||
ws_emergent = wb.create_sheet("Emergent Patterns")
|
||||
_create_emergent_sheet(ws_emergent, aggregation.emergent_patterns, header_font, header_fill)
|
||||
|
||||
# Save workbook
|
||||
output_path = output_dir / f"{batch_id}_analysis.xlsx"
|
||||
wb.save(output_path)
|
||||
|
||||
return output_path
|
||||
|
||||
|
||||
def _create_summary_sheet(ws, batch_id, aggregation, analyses, header_font, header_fill):
|
||||
"""Create summary sheet."""
|
||||
# Title
|
||||
ws["A1"] = "CXInsights Analysis Report"
|
||||
ws["A1"].font = Font(bold=True, size=16)
|
||||
ws.merge_cells("A1:D1")
|
||||
|
||||
ws["A2"] = f"Batch ID: {batch_id}"
|
||||
ws["A3"] = f"Generated: {datetime.utcnow().strftime('%Y-%m-%d %H:%M UTC')}"
|
||||
|
||||
# Metrics section
|
||||
row = 5
|
||||
ws[f"A{row}"] = "Key Metrics"
|
||||
ws[f"A{row}"].font = Font(bold=True, size=12)
|
||||
|
||||
metrics = [
|
||||
("Total Calls Analyzed", aggregation.total_calls_processed),
|
||||
("Successful Analyses", aggregation.successful_analyses),
|
||||
("Failed Analyses", aggregation.failed_analyses),
|
||||
("Success Rate", f"{aggregation.successful_analyses / aggregation.total_calls_processed * 100:.1f}%" if aggregation.total_calls_processed > 0 else "N/A"),
|
||||
]
|
||||
|
||||
if aggregation.rca_tree:
|
||||
tree = aggregation.rca_tree
|
||||
metrics.extend([
|
||||
("", ""),
|
||||
("Calls with Lost Sales Issues", tree.calls_with_lost_sales),
|
||||
("Calls with Poor CX Issues", tree.calls_with_poor_cx),
|
||||
("Calls with Both Issues", tree.calls_with_both),
|
||||
])
|
||||
|
||||
for i, (label, value) in enumerate(metrics):
|
||||
ws[f"A{row + 1 + i}"] = label
|
||||
ws[f"B{row + 1 + i}"] = value
|
||||
|
||||
# Top drivers section
|
||||
row = row + len(metrics) + 3
|
||||
ws[f"A{row}"] = "Top Lost Sales Drivers"
|
||||
ws[f"A{row}"].font = Font(bold=True, size=12)
|
||||
|
||||
for i, freq in enumerate(aggregation.lost_sales_frequencies[:5]):
|
||||
ws[f"A{row + 1 + i}"] = freq.driver_code
|
||||
ws[f"B{row + 1 + i}"] = f"{freq.call_rate:.1%}"
|
||||
|
||||
row = row + 7
|
||||
ws[f"A{row}"] = "Top Poor CX Drivers"
|
||||
ws[f"A{row}"].font = Font(bold=True, size=12)
|
||||
|
||||
for i, freq in enumerate(aggregation.poor_cx_frequencies[:5]):
|
||||
ws[f"A{row + 1 + i}"] = freq.driver_code
|
||||
ws[f"B{row + 1 + i}"] = f"{freq.call_rate:.1%}"
|
||||
|
||||
# Adjust column widths
|
||||
ws.column_dimensions["A"].width = 30
|
||||
ws.column_dimensions["B"].width = 20
|
||||
|
||||
|
||||
def _create_drivers_sheet(ws, frequencies, severities, header_font, header_fill):
|
||||
"""Create driver analysis sheet."""
|
||||
headers = [
|
||||
"Rank",
|
||||
"Driver Code",
|
||||
"Occurrences",
|
||||
"Calls Affected",
|
||||
"Call Rate",
|
||||
"Avg Confidence",
|
||||
"Severity Score",
|
||||
"Impact Level",
|
||||
]
|
||||
|
||||
# Write headers
|
||||
for col, header in enumerate(headers, 1):
|
||||
cell = ws.cell(row=1, column=col, value=header)
|
||||
cell.font = header_font
|
||||
cell.fill = header_fill
|
||||
|
||||
# Create severity lookup
|
||||
sev_map = {s.driver_code: s for s in severities}
|
||||
|
||||
# Write data
|
||||
for row, freq in enumerate(frequencies, 2):
|
||||
sev = sev_map.get(freq.driver_code)
|
||||
|
||||
ws.cell(row=row, column=1, value=row - 1)
|
||||
ws.cell(row=row, column=2, value=freq.driver_code)
|
||||
ws.cell(row=row, column=3, value=freq.total_occurrences)
|
||||
ws.cell(row=row, column=4, value=freq.calls_affected)
|
||||
ws.cell(row=row, column=5, value=f"{freq.call_rate:.1%}")
|
||||
ws.cell(row=row, column=6, value=f"{freq.avg_confidence:.2f}")
|
||||
ws.cell(row=row, column=7, value=f"{sev.severity_score:.1f}" if sev else "N/A")
|
||||
ws.cell(row=row, column=8, value=sev.impact_level.value if sev else "N/A")
|
||||
|
||||
# Adjust column widths
|
||||
for col in range(1, len(headers) + 1):
|
||||
ws.column_dimensions[get_column_letter(col)].width = 15
|
||||
|
||||
|
||||
def _create_calls_sheet(ws, analyses, header_font, header_fill):
|
||||
"""Create call details sheet."""
|
||||
headers = [
|
||||
"Call ID",
|
||||
"Outcome",
|
||||
"Status",
|
||||
"Lost Sales Drivers",
|
||||
"Poor CX Drivers",
|
||||
"Audio Duration (s)",
|
||||
]
|
||||
|
||||
# Write headers
|
||||
for col, header in enumerate(headers, 1):
|
||||
cell = ws.cell(row=1, column=col, value=header)
|
||||
cell.font = header_font
|
||||
cell.fill = header_fill
|
||||
|
||||
# Write data
|
||||
for row, analysis in enumerate(analyses, 2):
|
||||
lost_sales = ", ".join(d.driver_code for d in analysis.lost_sales_drivers)
|
||||
poor_cx = ", ".join(d.driver_code for d in analysis.poor_cx_drivers)
|
||||
|
||||
ws.cell(row=row, column=1, value=analysis.call_id)
|
||||
ws.cell(row=row, column=2, value=analysis.outcome.value)
|
||||
ws.cell(row=row, column=3, value=analysis.status.value)
|
||||
ws.cell(row=row, column=4, value=lost_sales or "-")
|
||||
ws.cell(row=row, column=5, value=poor_cx or "-")
|
||||
ws.cell(row=row, column=6, value=analysis.observed.audio_duration_sec)
|
||||
|
||||
# Adjust column widths
|
||||
ws.column_dimensions["A"].width = 15
|
||||
ws.column_dimensions["B"].width = 20
|
||||
ws.column_dimensions["C"].width = 12
|
||||
ws.column_dimensions["D"].width = 40
|
||||
ws.column_dimensions["E"].width = 40
|
||||
ws.column_dimensions["F"].width = 18
|
||||
|
||||
|
||||
def _create_emergent_sheet(ws, emergent_patterns, header_font, header_fill):
|
||||
"""Create emergent patterns sheet."""
|
||||
headers = [
|
||||
"Proposed Label",
|
||||
"Occurrences",
|
||||
"Avg Confidence",
|
||||
"Sample Evidence",
|
||||
]
|
||||
|
||||
# Write headers
|
||||
for col, header in enumerate(headers, 1):
|
||||
cell = ws.cell(row=1, column=col, value=header)
|
||||
cell.font = header_font
|
||||
cell.fill = header_fill
|
||||
|
||||
# Write data
|
||||
for row, pattern in enumerate(emergent_patterns, 2):
|
||||
evidence = "; ".join(pattern.get("sample_evidence", [])[:2])
|
||||
|
||||
ws.cell(row=row, column=1, value=pattern.get("proposed_label", "N/A"))
|
||||
ws.cell(row=row, column=2, value=pattern.get("occurrences", 0))
|
||||
ws.cell(row=row, column=3, value=f"{pattern.get('avg_confidence', 0):.2f}")
|
||||
ws.cell(row=row, column=4, value=evidence[:100] if evidence else "-")
|
||||
|
||||
# Adjust column widths
|
||||
ws.column_dimensions["A"].width = 30
|
||||
ws.column_dimensions["B"].width = 12
|
||||
ws.column_dimensions["C"].width = 15
|
||||
ws.column_dimensions["D"].width = 60
|
||||
Reference in New Issue
Block a user