Charts and figures

Parse handles charts and figures two ways. Specialized chart parsing reads a bar, line, or pie chart and returns its values as a table in the items tree, so a model can reason over the numbers instead of the pixels. Image output saves the figures themselves (cropped layout regions, embedded images, or full-page screenshots) as files you download by presigned URL.

When to use it

• Earnings decks, scientific papers, and dashboards where the data you need lives only in a chart.
• Multimodal pipelines that want one markdown blob plus a screenshot of every page.
• Figures and diagrams you want to show in a UI or pass to a vision model separately from the text.
• Self-contained markdown that carries its images inline.

Specialized chart parsing is on by default at the agentic_plus tier and opt-in on cost_effective and agentic. The fast tier runs no AI model, so it does not extract chart data.

Options

Option	Type	Default	What it does
processing_options.specialized_chart_parsing	"efficient", "agentic", or "agentic_plus"	unset (on by default for agentic_plus)	Extract chart data as structured tables in the items tree. Any of the three values turns it on. Retrieve with expand=["items"].
output_options.images_to_save	array of "screenshot", "embedded", "layout"	saves layout when the output links to cropped images	Which image files to save: full-page renders, images found in the document, or cropped figures and diagrams. Pass [] to save none. Retrieve with expand=["images_content_metadata"].
output_options.markdown.inline_images	boolean	unset	Embed images in the markdown itself instead of referencing separately saved files.
processing_options.ignore.ignore_text_in_image	boolean	unset	Skip OCR text from embedded images when it is noise, such as logos. Turns OCR off for the job, so born-digital files only.
input_options.presentation.skip_embedded_data	boolean	unset	For PPTX and Keynote, skip extracting the data behind native charts and keep only their visual.

The image_filenames query parameter on the result endpoint narrows images_content_metadata to the files you name.

Example

Parse with chart parsing on, save the cropped figures, and pull the first table off the chart page:

from llama_cloud import LlamaCloud

client = LlamaCloud()  # reads LLAMA_CLOUD_API_KEY from the environment

result = client.parsing.parse(
    file_id="FILE_ID",  # uploaded with client.files.create(file=..., purpose="parse")
    tier="agentic_plus",
    version="latest",
    processing_options={"specialized_chart_parsing": "agentic_plus"},
    output_options={"images_to_save": ["layout"]},
    expand=["items", "images_content_metadata"],
)

page = next(p for p in result.items.pages if p.success and p.page_number == 3)  # the chart page
tables = [item for item in page.items if item.type == "table"]
if tables:
    for row in tables[0].rows:
        print(row)

for image in result.images_content_metadata.images:
    print(f"{image.filename}: {image.presigned_url}")

What you get

With chart parsing, Parse often represents a chart’s data as a table item on that page. For the grouped bar chart in the chart example, the first row is the header and the rest are the series values:

['Fiscal Year', 'Budget Deficit (Billions of Dollars)', 'Net Operating Cost (Billions of Dollars)']
['2020', '$3,131.9', '$3,841.4']
['2021', '$2,775.6', '$3,094.9']
['2022', '$1,375.5', '$4,171.0']

Figures that stay as images appear in the items tree as image items, and images_content_metadata lists every saved file with a download URL:

{
  "images_content_metadata": {
    "total_count": 3,
    "images": [
      { "index": 0, "filename": "image_0.png", "category": "layout", "content_type": "image/png", "presigned_url": "https://..." }
    ]
  }
}

Presigned URLs expire. Download promptly, or call client.parsing.get(job_id=..., expand=["images_content_metadata"]) again for fresh ones; see fetch specific images to pull a subset by file name. For full-page screenshots, request expand=["metadata"] too and use each page’s original_orientation_angle when overlaying boxes; see Layout and bounding boxes.

See also

• Parse charts in PDFs and analyze with pandas: the full walk-through, from chart to DataFrame
• Recipes: per-page screenshots for a multimodal pipeline
• Configuring Parse: specialized chart parsing and image assets
• Response format: images for every field on an image entry
• Tables for the table formats chart data shares