VERIFICATIONChecked against current official documentation on 2026.08.04; hardware-specific performance is not generalized.

30-SECOND SUMMARY

What to take away

  • Distinguish text PDFs from scans.
  • Preserve page identifiers while chunking.
  • Check every important claim against the source page.
DOCUMENT 01

From PDF to grounded summary

Extraction quality comes first.

  1. 01
    EXTRACT

    Text or OCR

  2. 02
    CLEAN

    Keep pages and order

  3. 03
    SUMMARIZE

    Chunk then merge

  4. 04
    VERIFY

    Check source pages

Use it this way Track every derived copy for deletion.
SECTION 01

Identify the PDF type

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

SECTION 02

Inspect extraction

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

SECTION 03

Summarize in stages

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

SECTION 04

Verify and delete

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

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

Frequently asked questions

Can it handle scans?

Yes after OCR, but sample-check recognition errors.

Should I insert an entire long PDF?

Chunking or retrieval is often more reliable and memory-efficient.

Is a local summary automatically private?

No. Extraction files, indexes, logs, and backups also matter.

Primary sources

Check the original documentation for version-specific details.

Ollama Embeddings Open WebUI RAG

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