Summarize PDFs with Local AI

Selectable text usually indicates a text PDF; scanned pages require OCR. Tables and multi-column layouts can corrupt reading order.

The working rule for “Identify the PDF type” is: Distinguish text PDFs from scans. Exercise invalid input and interruption paths as well as the happy path, because application boundaries are where a working example most often fails.

For verification, save the model and runtime versions, source input, relevant settings, and observed output together. Repeat the step while changing only one factor, and record unexpected results and untested limits as carefully as successes before applying the guidance to private or production data.

Check repeated headers, line breaks, tables, footnotes, and page numbers before sending text to a model.

The working rule for “Inspect extraction” is: Preserve page identifiers while chunking. Exercise invalid input and interruption paths as well as the happy path, because application boundaries are where a working example most often fails.

Preserve the before-and-after state and the time of the check so that another run can reproduce the result. Include at least one failure condition—such as empty input, constrained resources, or a restart—to reveal the boundary of the step rather than documenting only the happy path.

Summarize page-aware chunks, then merge those summaries. For focused questions, retrieve only relevant chunks.

The working rule for “Summarize in stages” is: Check every important claim against the source page. Exercise invalid input and interruption paths as well as the happy path, because application boundaries are where a working example most often fails.

Define completion with an observable result instead of a general impression. Repeat the same input, and if the output changes, isolate whether the model, runtime settings, or source data changed before moving to the next stage.

Compare numbers and conclusions with source pages. Delete extracted text, indexes, chats, and backups—not only the original.

The working rule for “Verify and delete” is: Distinguish text PDFs from scans. Exercise invalid input and interruption paths as well as the happy path, because application boundaries are where a working example most often fails.

Use the checklist with a date and observed result beside every item. When one check fails, record its scope before continuing, then repeat the same input after the change; that turns a list of advice into evidence that the step actually works in this environment.

• Flag claims without a page
• Check table values manually
• Exclude unsupported conclusions
• Locate every sensitive copy