Update pdf_generator.py

pdf_generator.py

@@ -3,8 +3,8 @@ import re
 from reportlab.lib import colors
 from reportlab.lib.pagesizes import A4
 from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
-from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Flowable
-from reportlab.lib.units import mm
+from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, Flowable
+from reportlab.lib.units import mm, inch
 from reportlab.graphics.shapes import Drawing, Rect, String, Line
 
 class SliderFlowable(Flowable):
@@ -94,32 +94,22 @@ def create_page_template(canvas, doc):
     canvas.drawString(30, 20, f"Page {doc.page}")
     canvas.restoreState()
 
-def generate_pdf(pages, answers):
+def generate_pdf(session_state):
     buffer = io.BytesIO()
     doc = SimpleDocTemplate(buffer, pagesize=A4, rightMargin=20*mm, leftMargin=20*mm, topMargin=20*mm, bottomMargin=20*mm)
     styles = create_styles()
-    story = [Paragraph("AI Trust and Opacity Evaluation", styles['Title'])]
+    story = [Paragraph("Pilot Drafting", styles['Title'])]
 
-    for page in pages[:-1]:  # Skip the last page
+    for page in session_state.pages[:-1]:  # Skip the last page
         if 'input_key' in page and page['input_key'] is not None:
             story.append(Paragraph(page['title'], styles['Heading1']))
-            story.append(Paragraph(page['content'], styles['BodyText']))
 
-            answer = answers.get(page['input_key'], "")
-            if isinstance(answer, list):
-                answer = ', '.join(answer)
-
-            if page.get('input_type') == 'combined':
-                option = answers.get(page['input_key'], "")
-                conclusion = answers.get(f"{page['input_key']}_conclusion", "")
-                story.append(Paragraph(f"<b>Option selected:</b> {option}", styles['Answer']))
-                story.append(Paragraph(f"<b>Conclusion:</b> {conclusion}", styles['Answer']))
-            else:
-                story.append(Paragraph(f"<b>Answer:</b> {answer}", styles['Answer']))
-
-            # Add quantitative criteria visualization if applicable
-            if page['input_key'] in ['technological_literacy', 'cognitive_mismatch']:
-                story.extend(process_quantitative_criteria(answer, styles))
+            if page['input_key'] == 'workload_scope':
+                story.extend(process_workload_scope(session_state, styles))
+            elif page['input_key'] == 'useful_assets':
+                story.extend(process_useful_assets(session_state, styles))
+            elif page['input_key'] == 'pilot_evaluation':
+                story.extend(process_pilot_evaluation(session_state, styles))
 
             story.append(Spacer(1, 12))
 
@@ -127,36 +117,98 @@ def generate_pdf(pages, answers):
     buffer.seek(0)
     return buffer
 
-def process_quantitative_criteria(answer, styles):
+def process_workload_scope(session_state, styles):
+    story = []
+    answers = session_state.answers['workload_scope']
+
+    story.append(Paragraph("Feature Prioritization", styles['Heading2']))
+    for i, feature in enumerate(answers['feature_prioritization']):
+        lines = feature.split('\n')
+        for line in lines:
+            story.append(Paragraph(f"<b>Feature {i+1}</b>: {line}", styles['Answer']))
+
+    # story.append(Paragraph("Preferred Start Period", styles['Heading2']))
+    # story.append(Paragraph(str(answers['preferred_start_period']), styles['Answer']))
+    story.append(Paragraph("Preferred Start Period", styles['Heading2']))
+    story.append(Paragraph(f"<b>{answers['preferred_start_period'][0]}</b> - <b>{answers['preferred_start_period'][1]}</b>", styles['Answer']))
+
+    story.append(Paragraph("Team Composition", styles['Heading2']))
+    for team_member in ['partner', 'ibm']:
+        lines = answers['team_composition'][team_member].split('\n')
+        for line in lines:
+            story.append(Paragraph(f"<b>{team_member.capitalize()}</b>: {line}", styles['Answer']))
+
+    return story
+
+def process_useful_assets(session_state, styles):
+    story = []
+    answers = session_state.answers['useful_assets']
+
+    story.append(Paragraph("Solution Elements", styles['Heading2']))
+    for element in answers['solution_elements']:
+        story.append(Paragraph(element, styles['Answer']))
+
+    story.append(Paragraph("IBM Software", styles['Heading2']))
+    for software in answers['ibm_software']:
+        story.append(Paragraph(software, styles['Answer']))
+
+    story.append(Paragraph("Open Source Supports", styles['Heading2']))
+    for support in answers['open_source_supports']:
+        story.append(Paragraph(support, styles['Answer']))
+
+    return story
+
+def process_pilot_evaluation(session_state, styles):
+    story = []
+    answers = session_state.answers['useful_assets']
+
+    story.extend(process_validation_criteria(answers, styles))
+
+    return story
+
+def process_validation_criteria(session_state, styles):
     story = []
-    lines = answer.split('\n')
-    for line in lines:
-        parsed = parse_quantitative_criteria(line)
+
+    # Qualitative Criteria
+    story.append(Paragraph("Qualitative Criteria:", styles['Heading2']))
+    for i, criterion in enumerate(session_state.get('qualitative', [])):
+        description = session_state.get(f'qual_desc_{i}', '')
+        story.append(Paragraph(f"<b>{criterion}</b>: <font face='Helvetica' size=11 color='#350863'>{description}</font>", styles['Answer']))
+
+    # Quantitative Criteria
+    story.append(Paragraph("Quantitative Criteria:", styles['Heading2']))
+    for i, criterion in enumerate(session_state.get('quantitative', [])):
+        parsed = parse_quantitative_criteria(criterion)
         if parsed:
-            name, value, min_val, max_val, is_percentage = parsed
+            name, min_val, max_val, is_percentage, is_integer = parsed
+            value = session_state.get(f'quant_value_{i}', min_val)
+
             if is_percentage:
                 slider = SliderFlowable(name, value*100, min_val*100, max_val*100, is_percentage=True)
             else:
                 slider = SliderFlowable(name, value, min_val, max_val, is_percentage=False)
+
             story.append(slider)
+            story.append(Paragraph(f"<b>{name}</b>: {value:.2f}", styles['Answer']))
+
     return story
 
 def parse_quantitative_criteria(input_string):
-    match = re.match(r'(.+):\s*([-+]?(?:\d*\.*\d+)(?:%)?)(?:\s*\[([-+]?(?:\d*\.*\d+)(?:%)?)\s*-\s*([-+]?(?:\d*\.*\d+)(?:%)?)?\])?', input_string)
+    match = re.match(r'(.+)\[([-+]?(?:\d*\.*\d+)(?:%)?)\s*-\s*([-+]?(?:\d*\.*\d+)(?:%)?)?\]', input_string)
     if match:
-        name, value, min_val, max_val = match.groups()
+        name, min_val, max_val = match.groups()
         name = name.strip()
 
         # Handle percentage inputs
-        is_percentage = '%' in value or '%' in min_val or '%' in max_val
-        value = float(value.rstrip('%'))
-        min_val = float(min_val.rstrip('%') if min_val else 0)
-        max_val = float(max_val.rstrip('%') if max_val else 100)
+        is_percentage = '%' in min_val or '%' in max_val
+        min_val = float(min_val.rstrip('%'))
+        max_val = float(max_val.rstrip('%'))
 
         if is_percentage:
-            value /= 100
             min_val /= 100
             max_val /= 100
 
-        return name, value, min_val, max_val, is_percentage
+        is_integer = '.' not in input_string or (min_val.is_integer() and max_val.is_integer())
+
+        return name, min_val, max_val, is_percentage, is_integer
     return None