Building Agentic Document Intelligence Pipelines: Creating Scientific Figures with AutoFigure

heading("4. Creating a custom reference figure")
reference_dir = OUTPUT_ROOT / "01_custom_references"
reference_dir.mkdir(parents=True, exist_ok=True)
reference_path = reference_dir / "reference_architecture_style.png"
W, H = 1333, 750
img = Image.new("RGB", (W, H), "white")
draw = ImageDraw.Draw(img)
try:
   title_font = ImageFont.truetype("DejaVuSans-Bold.ttf", 36)
   box_font = ImageFont.truetype("DejaVuSans-Bold.ttf", 24)
   small_font = ImageFont.truetype("DejaVuSans.ttf", 18)
except Exception:
   title_font = None
   box_font = None
   small_font = None
draw.text(
   (W // 2, 55),
   "Reference Layout: Modular Scientific Pipeline",
   anchor="mm",
   fill="black",
   font=title_font,
)
boxes = [
   (90, 215, 290, 120, "Input", "documents"),
   (365, 215, 290, 120, "Planner", "route by task"),
   (640, 215, 290, 120, "Experts", "summary / table / vision"),
   (915, 215, 290, 120, "Verifier", "grounded output"),
]
for i, (x, y, bw, bh, title, subtitle) in enumerate(boxes):
   draw.rounded_rectangle(
       [x, y, x + bw, y + bh],
       radius=22,
       fill=(245, 245, 245),
       outline=(20, 20, 20),
       width=3,
   )
   draw.text(
       (x + bw / 2, y + 45),
       title,
       anchor="mm",
       fill="black",
       font=box_font,
   )
   draw.text(
       (x + bw / 2, y + 82),
       subtitle,
       anchor="mm",
       fill=(70, 70, 70),
       font=small_font,
   )
   if i < len(boxes) - 1:
       ax = x + bw + 20
       ay = y + bh / 2
       bx = boxes[i + 1][0] - 20
       by = ay
       draw.line([ax, ay, bx, by], fill="black", width=5)
       draw.polygon(
           [(bx, by), (bx - 18, by - 10), (bx - 18, by + 10)],
           fill="black",
       )
draw.rounded_rectangle(
   [180, 500, 1150, 585],
   radius=24,
   fill=(252, 252, 252),
   outline=(80, 80, 80),
   width=2,
)
draw.text(
   (665, 542),
   "Design cue: aligned modules, sparse labels, strong flow direction, clean academic styling",
   anchor="mm",
   fill=(40, 40, 40),
   font=small_font,
)
img.save(reference_path)
print(f"Custom reference saved: {reference_path}")
display_file_if_possible(reference_path, "Custom reference figure")
heading("5. Configuring API-backed AutoFigure")
API_KEY = collect_api_key(PROVIDER)
if not API_KEY:
   print("No API key provided. Cloud generation sections will be skipped.")
else:
   print(f"Provider: {PROVIDER}")
   print(f"Generation model: {GENERATION_MODEL}")
   print("API key received. The key is not printed.")
config = None
agent = None
if API_KEY:
   config = Config(
       generation_api_key=API_KEY,
       generation_provider=PROVIDER,
       generation_model=GENERATION_MODEL,
       methodology_api_key=API_KEY,
       methodology_provider=PROVIDER,
       methodology_model=GENERATION_MODEL,
       enhancement_api_key=API_KEY if RUN_IMAGE_ENHANCEMENT else None,
       enhancement_provider=PROVIDER,
       enhancement_model=os.environ.get(
           "AUTOFIGURE_ENHANCEMENT_MODEL",
           "google/gemini-3.1-flash-image-preview"
           if PROVIDER == "openrouter"
           else "gemini-3.1-flash-image-preview",
       ),
       max_iterations=MAX_ITERATIONS,
       quality_threshold=QUALITY_THRESHOLD,
       output_dir=str(OUTPUT_ROOT / "02_text_to_figure"),
       custom_references=[str(reference_path)],
       art_style=ART_STYLE,
   )
   validation_errors = config.validate()
   print(f"Config validation errors: {validation_errors if validation_errors else 'none'}")
   print(f"References found by config: {len(config.get_references())}")
   agent = AutoFigureAgent(config)
heading("6. Prompt template preview")
prompt_preview = get_initial_prompt_template(
   topic="paper",
   content=FIGURE_DESCRIPTION[:2500],
   output_format="svg",
)
print(prompt_preview[:2500])
print("\n... prompt preview truncated ...")
if API_KEY and RUN_TEXT_TO_FIGURE:
   heading("7. Running text-to-figure generation")
   text_output_dir = OUTPUT_ROOT / "02_text_to_figure"
   text_output_dir.mkdir(parents=True, exist_ok=True)
   text_result = agent.generate(
       description=FIGURE_DESCRIPTION,
       max_iterations=MAX_ITERATIONS,
       quality_threshold=QUALITY_THRESHOLD,
       output_format=TEXT_OUTPUT_FORMAT,
       enable_enhancement=RUN_IMAGE_ENHANCEMENT,
       art_style=ART_STYLE,
       enhancement_input_type="code2prompt",
       enhancement_count=1,
       custom_references=[str(reference_path)],
       output_dir=str(text_output_dir),
       topic="paper",
   )
   summarize_generation_result(text_result, "Text-to-Figure Result")
else:
   print("Skipping text-to-figure generation.")