Utilizing Elevate to Flip Analysis PDFs into Structured JSON with Managed, Schema-Guided Discipline-Degree Analysis

def render_pdf(d, path):
   """Draw a practical 3-page report. Web page breaks are compelled so the headline metric on
   web page 1 (summary) is bodily separated from the outcomes desk on web page 3."""
   from reportlab.lib.pagesizes import LETTER
   from reportlab.lib.types import getSampleStyleSheet, ParagraphStyle
   from reportlab.lib.items import inch
   from reportlab.lib import colours
   from reportlab.platypus import (SimpleDocTemplate, Paragraph, Spacer,
                                   Desk, TableStyle, PageBreak)
   ss = getSampleStyleSheet()
   H1   = ParagraphStyle("H1", mum or dad=ss["Title"], fontSize=16, main=20, spaceAfter=6)
   AUTH = ParagraphStyle("AUTH", mum or dad=ss["Normal"], fontSize=9.5, textColor=colours.gray, spaceAfter=10)
   H2   = ParagraphStyle("H2", mum or dad=ss["Heading2"], fontSize=12, spaceBefore=8, spaceAfter=4)
   BODY = ParagraphStyle("BODY", mum or dad=ss["Normal"], fontSize=10, main=14, spaceAfter=6)
   sota_phrase = (f"surpassing the earlier better of {d['prior_best']}"
                  if d["beats_sota"] else
                  f"approaching however not exceeding the earlier better of {d['prior_best']}")
   authors_line = ", ".be part of(f"{n} ({a})" for (n, a) in d["authors"])
   story = []
   story += [Paragraph(d["title"], H1), Paragraph(authors_line, AUTH), Paragraph("Summary", H2)]
   story += [Paragraph(
       f"We introduce {d['method']}, a mannequin for {d['task']}. On the {d['primary_benchmark']} "
       f"benchmark, {d['method']} attains {d['test_acc']} {d['metric_name']} on the held-out "
       f"check set, {sota_phrase}. Our {d['params_m']}M-parameter mannequin is evaluated throughout "
       f"{len(d['datasets'])} datasets ({', '.be part of(d['datasets'])}). "
       f"Intensive ablations affirm the contribution of every element.", BODY)]
   story += [Paragraph("Keywords", H2),
             Paragraph(f"{d['task']}; illustration studying; {d['primary_benchmark']}", BODY),
             PageBreak()]
   story += [Paragraph("1  Method and Training Details", H2)]
   story += [Paragraph(
       f"{d['method']} is educated end-to-end with the {d['optimizer']} optimizer. "
       f"We tune on a validation break up and report last numbers on the check break up. "
       f"The total coaching configuration is summarized in Desk 1.", BODY)]
   hp = [["Hyperparameter", "Value"],
         ["Optimizer", d["optimizer"]],
         ["Learning rate", str(d["lr"])],
         ["Batch size", str(d["batch"])],
         ["Epochs", str(d["epochs"])],
         ["Parameters", f"{d['params_m']}M"]]
   t1 = Desk(hp, colWidths=[2.4 * inch, 2.0 * inch])
   t1.setStyle(TableStyle([
       ("BACKGROUND", (0, 0), (-1, 0), colors.HexColor("#2b3a67")),
       ("TEXTCOLOR", (0, 0), (-1, 0), colors.white),
       ("FONTSIZE", (0, 0), (-1, -1), 9.5),
       ("GRID", (0, 0), (-1, -1), 0.4, colors.grey),
       ("ROWBACKGROUNDS", (0, 1), (-1, -1), [colors.white, colors.HexColor("#eef1f8")]),
       ("LEFTPADDING", (0, 0), (-1, -1), 8), ("TOPPADDING", (0, 0), (-1, -1), 4),
       ("BOTTOMPADDING", (0, 0), (-1, -1), 4)]))
   story += [Spacer(1, 4), t1, Spacer(1, 6),
             Paragraph("Table 1. Training configuration.", BODY),
             Paragraph("2  Datasets", H2),
             Paragraph(
                 f"We evaluate on {', '.join(d['datasets'])}. {d['primary_benchmark']} is our "
                 f"main benchmark; the remaining datasets are used for generalization "
                 f"research.", BODY),
             PageBreak()]
   story += [Paragraph("3  Results", H2)]
   res = [["Method", f"Val. {d['metric_name']}", f"Check {d['metric_name']}"],
          [f"{d['baseline_name']} (baseline)", str(d["baseline_val"]), str(d["baseline_test"])],
          [f"{d['method']} (ours)", str(d["val_acc"]), str(d["test_acc"])]]
   t2 = Desk(res, colWidths=[2.6 * inch, 1.7 * inch, 1.7 * inch])
   t2.setStyle(TableStyle([
       ("BACKGROUND", (0, 0), (-1, 0), colors.HexColor("#7a2e2e")),
       ("TEXTCOLOR", (0, 0), (-1, 0), colors.white),
       ("FONTSIZE", (0, 0), (-1, -1), 9.5),
       ("GRID", (0, 0), (-1, -1), 0.4, colors.grey),
       ("FONTNAME", (0, 2), (-1, 2), "Helvetica-Bold"),
       ("ROWBACKGROUNDS", (0, 1), (-1, -1), [colors.white, colors.HexColor("#f7eeee")]),
       ("LEFTPADDING", (0, 0), (-1, -1), 8), ("TOPPADDING", (0, 0), (-1, -1), 4),
       ("BOTTOMPADDING", (0, 0), (-1, -1), 4)]))
   story += [Spacer(1, 4), t2, Spacer(1, 6),
             Paragraph(f"Table 2. Results on {d['primary_benchmark']}. "
                       f"Greatest check lead to daring.", BODY),
             Paragraph("4  Limitations", H2)]
   for lim in d["limitations"]:
       story += [Paragraph("• " + lim, BODY)]
   story += [Paragraph("5  Funding and Code Availability", H2),
             Paragraph(d["funding_note"], BODY)]
   SimpleDocTemplate(path, pagesize=LETTER,
                     topMargin=0.8 * inch, bottomMargin=0.8 * inch,
                     leftMargin=0.9 * inch, rightMargin=0.9 * inch).construct(story)
print("STEP 3/7 · Producing artificial report PDFs…")
CORPUS = []
for i, d in enumerate(DOCS):
   path = f"/content material/report_{i}.pdf" if os.path.isdir("/content material") else f"report_{i}.pdf"
   render_pdf(d, path)
   CORPUS.append((d, ground_truth(d), path))
   print(f"     ✓ {os.path.basename(path)}  —  {d['method']}")
print()
if SHOW_FIRST_PAGE:
   strive:
       import pypdfium2 as pdfium, matplotlib.pyplot as plt
       pg  = pdfium.PdfDocument(CORPUS[0][2])[0]
       img = pg.render(scale=2.0).to_pil()
       plt.determine(figsize=(6.4, 8.3)); plt.imshow(img); plt.axis("off")
       plt.title("What carry reads — web page 1 of report_0.pdf", fontsize=10); plt.present()
   besides Exception as e:
       print("     (web page preview skipped:", e, ")n")