Professional Reporting: Metadata, Taxonomy, Full-Text Viewer, PDF Export (#11)

backend/app/api/routes.py

@@ -237,6 +237,7 @@ async def analyze_paper(
                             {
                                 "url": w.url, "title": w.title, "snippet": w.snippet,
                                 "matched_text": w.matched_text, "similarity": w.similarity,
+                                "match_type": "uncited",
                             }
                             for w in (web_result.matches if web_result else [])
                         ],
@@ -277,6 +278,9 @@ async def analyze_paper(
 
         result = AnalysisResult(
             filename=record.filename,
+            author_name=record.author_name,
+            institution=record.institution,
+            full_text=record.full_text,
             analyzed_at=(record.analyzed_at or datetime.now(timezone.utc)).isoformat(),
             word_count=record.word_count,
             section_count=len(sections_payload),
@@ -604,6 +608,7 @@ async def _process_analysis_task(task_id: str):
                             {
                                 "url": w.url, "title": w.title, "snippet": w.snippet,
                                 "matched_text": w.matched_text, "similarity": w.similarity,
+                                "match_type": "uncited",
                             }
                             for w in (web_result.matches if web_result else [])
                         ],

backend/app/core/database.py

@@ -96,6 +96,9 @@ def _apply_analysis_result_migrations(engine) -> None:
         ("methodology_fingerprint_score", "INTEGER"),
         ("provenance_score", "INTEGER"),
         ("pcv_details", "JSON"),
+        ("author_name", "TEXT"),
+        ("institution", "TEXT"),
+        ("full_text", "TEXT"),
     ]
     try:
         from sqlalchemy import inspect

backend/app/models/database.py

@@ -18,6 +18,9 @@ class AnalysisResult(Base):
 
     # File metadata
     filename = Column(String(255), nullable=False, index=True)
+    author_name = Column(String(255), nullable=True)
+    institution = Column(String(255), nullable=True)
+    full_text = Column(JSON, nullable=True)
     file_size = Column(Integer, nullable=False)  # bytes
     file_hash = Column(String(64), unique=True, index=True)  # SHA256
     word_count = Column(Integer, nullable=False, default=0)
@@ -63,6 +66,9 @@ def to_dict(self):
         return {
             "id": self.id,
             "filename": self.filename,
+            "author_name": self.author_name,
+            "institution": self.institution,
+            "full_text": self.full_text,
             "file_size": self.file_size,
             "word_count": self.word_count,
             "plagiarism_score": self.plagiarism_score,

backend/app/models/schemas.py

@@ -7,6 +7,8 @@ class PlagiarismMatchSchema(BaseModel):
     similarity: float = Field(..., ge=0, le=100)
     source: str
     matched_text: str
+    match_type: str = "uncited"  # 'cited', 'uncited', or 'internal'
+
 
 
 class PlagiarismModuleResult(BaseModel):
@@ -95,6 +97,9 @@ class ScoreContributions(BaseModel):
 
 class AnalysisResult(BaseModel):
     filename: str
+    author_name: Optional[str] = None
+    institution: Optional[str] = None
+    full_text: Optional[str] = None
     analyzed_at: str
     word_count: int
     section_count: int

backend/app/services/plagiarism.py

@@ -33,6 +33,8 @@ class SimilarityMatch:
     source_corpus: str
     similarity: float
     matched_text: str
+    match_type: str = "uncited"  # 'cited', 'uncited', or 'internal'
+
 
 
 @dataclass
@@ -278,6 +280,7 @@ def _detect_internal_duplication(sections: List["Section"]) -> List[SimilarityMa
                         source_corpus="self",
                         similarity=round(jacc * 100, 1),
                         matched_text=text_i[:180],
+                        match_type="internal",
                     )
                 )
     return matches

backend/app/services/report.py

@@ -1,107 +1,145 @@
 """PDF evidence report generation with per-module findings."""
 import json
 import logging
+from pathlib import Path
+from datetime import datetime, timezone
 from reportlab.lib.pagesizes import A4
-from reportlab.lib.units import cm
+from reportlab.lib.units import cm, inch
 from reportlab.lib import colors
-from reportlab.pdfgen import canvas
+from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
+from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, PageBreak
+from reportlab.lib.enums import TA_CENTER, TA_LEFT
 
 from ..core.config import settings
 
 logger = logging.getLogger(__name__)
 
-RIGHT, TOP_MARGIN = A4[0] - 2 * cm, A4[1] - 2 * cm
-
-
-def _wrap(text: str, max_width, font, fontsize, canvas_obj):
-    """Wrap text into lines that fit max_width, return list of lines."""
-    canvas_obj.setFont(font, fontsize)
-    words = text.split()
-    lines, cur = [], ""
-    for word in words:
-        trial = (cur + " " + word).strip()
-        if canvas_obj.stringWidth(trial, font, fontsize) <= max_width:
-            cur = trial
-        else:
-            if cur:
-                lines.append(cur)
-            cur = word
-    if cur:
-        lines.append(cur)
-    return lines
-
-
-def write_pdf_report(doc, record, breakdown, citation_result, statistics_result, writing_result, report_name):
-    """Write a detailed evidence PDF for the analysis record."""
-    output_path = settings.REPORTS_DIR / report_name
+def write_pdf_report(doc, record, breakdown, citation_result, statistics_result, writing_quality_result, filename):
+    """Generate a professional research integrity report with cover page."""
+    output_path = settings.REPORTS_DIR / filename
     settings.REPORTS_DIR.mkdir(parents=True, exist_ok=True)
 
-    c = canvas.Canvas(str(output_path), pagesize=A4)
-    width = A4[0]
-    y = TOP_MARGIN
+    doc_pdf = SimpleDocTemplate(
+        str(output_path), 
+        pagesize=A4, 
+        leftMargin=2*cm, rightMargin=2*cm, 
+        topMargin=2*cm, bottomMargin=2*cm
+    )
+    styles = getSampleStyleSheet()
+
+    # Custom Styles
+    title_style = ParagraphStyle('TitleStyle', parent=styles['Title'], fontSize=24, spaceAfter=30, alignment=TA_CENTER)
+    subtitle_style = ParagraphStyle('SubtitleStyle', parent=styles['Normal'], fontSize=14, spaceAfter=12, alignment=TA_CENTER, textColor=colors.grey)
+    heading_style = ParagraphStyle('HeadingStyle', parent=styles['Heading1'], fontSize=16, spaceBefore=20, spaceAfter=12, textColor=colors.HexColor("#1e293b"))
+
+    story = []
 
-    # Header
-    c.setFont("Helvetica-Bold", 16)
-    c.drawString(2 * cm, y, "VeriPaper — Research Verification Report")
-    y -= 10
-    c.setFont("Helvetica", 9)
-    c.drawString(2 * cm, y, f"File: {record.filename}  |  {record.word_count} words  |  Analyzed {record.analyzed_at:%Y-%m-%d %H:%M UTC}")
-    y -= 18
+    # --- COVER PAGE ---
+    story.append(Spacer(1, 4 * cm))
+    story.append(Paragraph("RESEARCH INTEGRITY REPORT", title_style))
+    story.append(Paragraph("VeriPaper Autonomous Verification Platform", subtitle_style))
+    story.append(Spacer(1, 2 * cm))
+
+    meta_data = [
+        [Paragraph("<b>Document:</b>", styles['Normal']), Paragraph(record.filename, styles['Normal'])],
+        [Paragraph("<b>Author:</b>", styles['Normal']), Paragraph(record.author_name or "Not Specified", styles['Normal'])],
+        [Paragraph("<b>Institution:</b>", styles['Normal']), Paragraph(record.institution or "Not Specified", styles['Normal'])],
+        [Paragraph("<b>Analysis Date:</b>", styles['Normal']), Paragraph(record.analyzed_at.strftime('%B %d, %Y'), styles['Normal'])],
+        [Paragraph("<b>Report ID:</b>", styles['Normal']), Paragraph(f"VP-{record.id:06d}", styles['Normal'])],
+    ]
+    meta_table = Table(meta_data, colWidths=[4 * cm, 10 * cm])
+    meta_table.setStyle(TableStyle([
+        ('VALIGN', (0, 0), (-1, -1), 'TOP'),
+        ('BOTTOMPADDING', (0, 0), (-1, -1), 8),
+    ]))
+    story.append(meta_table)
+
+    story.append(Spacer(1, 4 * cm))
+
+    # Credibility Badge
+    score_color = colors.green if record.overall_research_credibility >= 75 else (colors.orange if record.overall_research_credibility >= 50 else colors.red)
+    badge_data = [[Paragraph(f"<font size=12 color=white>OVERALL CREDIBILITY</font><br/><font size=36 color=white><b>{record.overall_research_credibility}%</b></font>", ParagraphStyle('Badge', alignment=TA_CENTER))]]
+    badge = Table(badge_data, colWidths=[6 * cm])
+    badge.setStyle(TableStyle([
+        ('BACKGROUND', (0, 0), (-1, -1), score_color),
+        ('ROUNDEDCORNERS', [10, 10, 10, 10]),
+        ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
+        ('VALIGN', (0, 0), (-1, -1), 'MIDDLE'),
+        ('BOTTOMPADDING', (0, 0), (-1, -1), 20),
+        ('TOPPADDING', (0, 0), (-1, -1), 20),
+    ]))
+    story.append(badge)
+
+    story.append(PageBreak())
 
-    # Verdict box
-    verdict_colors = {"Credible": colors.green, "Needs review": colors.orange, "High risk": colors.red}
-    color = verdict_colors.get(record.verdict, colors.grey)
-    c.setFillColor(color)
-    c.roundRect(2 * cm, y - 30, width - 4 * cm, 36, 6, fill=1, stroke=0)
-    c.setFillColor(colors.white)
-    c.setFont("Helvetica-Bold", 13)
-    c.drawString(2 * cm + 12, y - 22, f"{record.verdict} — overall credibility {record.overall_research_credibility}/100")
-    c.setFont("Helvetica", 9)
-    c.drawCentredString(width / 2, y - 14, "Scores are assistive likelihood signals, not conclusive proof of misconduct.")
-    y -= 52
-    c.setFillColor(colors.black)
+    # --- EXECUTIVE SUMMARY ---
+    story.append(Paragraph("1. Integrity Overview", heading_style))
+
+    summary_text = f"The document '{record.filename}' has undergone a comprehensive multi-module verification. "
+    if record.overall_research_credibility >= 75:
+        summary_text += "The analysis indicates a high level of research integrity with standard citation patterns and natural statistical distributions."
+    elif record.overall_research_credibility >= 50:
+        summary_text += "The analysis identifies moderate risks that require manual review, particularly in the areas of citation alignment and statistical consistency."
+    else:
+        summary_text += "Significant integrity risks were detected. Multiple forensic modules flagged irregularities that deviate from standard academic writing and reporting."
+
+    story.append(Paragraph(summary_text, styles['Normal']))
+    story.append(Spacer(1, 0.5 * cm))
+
+    # Verdict Box
+    verdict_data = [[Paragraph(f"<b>VERDICT: {record.verdict.upper()}</b>", ParagraphStyle('Verdict', textColor=colors.white, alignment=TA_CENTER))]]
+    verdict_table = Table(verdict_data, colWidths=[14 * cm])
+    verdict_table.setStyle(TableStyle([
+        ('BACKGROUND', (0, 0), (-1, -1), score_color),
+        ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
+        ('PADDING', (0, 0), (-1, -1), 10),
+    ]))
+    story.append(verdict_table)
+    story.append(Spacer(1, 1 * cm))
 
-    sections = [
-        ("AI Generation Detection", [
-            f"AI-likelihood score: {record.ai_probability}% (confidence: {record.ai_confidence})",
-            f"Engine: {record.ai_engine}",
-        ]),
-        ("Similarity (Plagiarism) Check", [
-            f"Similarity score: {record.plagiarism_score}/100",
-        ] + ([f"Match: {m['title']} ({m['similarity']}%)" for m in
-              (json.loads(record.plagiarism_matches) if record.plagiarism_matches else [])][:5])),
-        ("Citation Validation", [
-            f"Validity score: {record.citation_validity_score}/100",
-            f"DOIs checked: {json.loads(record.citation_details).get('total_dois', 0) if record.citation_details else 0} "
-            f"(valid: {json.loads(record.citation_details).get('valid_dois', 0) if record.citation_details else 0})",
-        ]),
-        ("Statistical Integrity", [
-            f"Risk score: {record.statistical_risk_score}/100 — {statistics_result.summary}",
-        ] + [f"• {f.category}: {f.detail}" for f in statistics_result.findings][:4]),
-        ("Academic Writing Standards", [
-            f"Writing quality: {record.writing_quality_score}/100 ({writing_result.grade})",
-        ] + [f"• {'PASS' if ck['passed'] else 'FAIL'} {ck['name']}: {ck['detail']}" for ck in
-             (json.loads(record.writing_checks) if record.writing_checks else [])]),
+    # --- MODULE DETAILS ---
+    story.append(Paragraph("2. Detailed Module Findings", heading_style))
+
+    modules = [
+        ("AI Detection", f"{record.ai_probability}% probability (Engine: {record.ai_engine})"),
+        ("Similarity Check", f"{record.plagiarism_score}% overlap with indexed corpus"),
+        ("Citation Validity", f"{record.citation_validity_score}% CrossRef validation score"),
+        ("Statistical Integrity", f"{record.statistical_risk_score}% risk based on distribution forensics"),
+        ("Writing Quality", f"{record.writing_quality_score}% adherence to academic standards"),
     ]
+
+    mod_table = Table(modules, colWidths=[5 * cm, 9 * cm])
+    mod_table.setStyle(TableStyle([
+        ('GRID', (0, 0), (-1, -1), 0.5, colors.grey),
+        ('BACKGROUND', (0, 0), (0, -1), colors.whitesmoke),
+        ('PADDING', (0, 0), (-1, -1), 6),
+        ('VALIGN', (0, 0), (-1, -1), 'MIDDLE'),
+    ]))
+    story.append(mod_table)
+
+    # --- SIMILARITY TAXONOMY ---
+    story.append(Paragraph("3. Similarity & Attribution Taxonomy", heading_style))
+    plag_matches = json.loads(record.plagiarism_matches) if record.plagiarism_matches else []
+    if plag_matches:
+        match_data = [["Source Title", "Similarity", "Type"]]
+        for m in plag_matches[:10]:
+            m_type = m.get("match_type", "uncited").capitalize()
+            match_data.append([m["title"], f"{m['similarity']}%", m_type])
+
+        t = Table(match_data, colWidths=[8 * cm, 3 * cm, 3 * cm])
+        t.setStyle(TableStyle([
+            ('BACKGROUND', (0, 0), (-1, 0), colors.HexColor("#f1f5f9")),
+            ('GRID', (0, 0), (-1, -1), 0.5, colors.grey),
+            ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
+            ('PADDING', (0, 0), (-1, -1), 6),
+        ]))
+        story.append(t)
+    else:
+        story.append(Paragraph("No significant similarities detected.", styles['Normal']))
 
-    for title, lines in sections:
-        c.setFont("Helvetica-Bold", 11)
-        c.drawString(2 * cm, y, title)
-        y -= 13
-        c.setFont("Helvetica", 9)
-        for line in lines:
-            wrapped = _wrap(line, width - 4 * cm, "Helvetica", 9, c)
-            for wline in wrapped:
-                if y < 3 * cm:
-                    c.showPage()
-                    y = TOP_MARGIN
-                    c.setFont("Helvetica", 9)
-                c.drawString(2 * cm + 6, y, wline)
-                y -= 12
-        y -= 8
+    # Footer
+    story.append(Spacer(1, 2 * cm))
+    story.append(Paragraph("<i>Generated by VeriPaper Autonomous Platform. This report is intended for academic assistance only.</i>", styles['Normal']))
 
-    c.setFont("Helvetica-Oblique", 8)
-    c.drawString(2 * cm, 1.4 * cm, "Generated by VeriPaper. This report is assistive evidence only.")
-    c.showPage()
-    c.save()
-    logger.info("Report written: %s", output_path)
+    doc_pdf.build(story)
+    logger.info("Professional report written: %s", output_path)

backend/frontend/dist/index.html

@@ -5,8 +5,8 @@
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>VeriPaper — Research Paper Verification Suite</title>
     <meta name="description" content="VeriPaper checks research papers in seconds: plagiarism, AI authorship, citation authenticity, statistical integrity, and academic writing standards. Upload PDF, DOCX, or TXT and get a credibility score with plain-language explanations." />
-    <script type="module" crossorigin src="/static/assets/index-BOzsEJay.js"></script>
-    <link rel="stylesheet" crossorigin href="/static/assets/index-DO6YDTte.css">
+    <script type="module" crossorigin src="/static/assets/index-BzxcpKo6.js"></script>
+    <link rel="stylesheet" crossorigin href="/static/assets/index-BWQc25CZ.css">
   </head>
   <body class="bg-slate-950 text-slate-100">
     <div id="root"></div>