How to Summarise an Arabic PDF With AI Without Invented Content: Steps and a Ready Prompt

First check whether your PDF has a real text layer, because most Arabic summarisation failures start right there. Once you verify the file, choose your tool based on the task: for long sources or several files where you want answers you can check page by page against direct citations, use Gemini Notebook (the tool formerly called NotebookLM). For one file in a quick chat session, use ChatGPT, Claude, or the Gemini app. If you want a fast query with no sign-up required, use ChatPDF. Skip the check and you may be feeding the model garbled characters, which is an open invitation to invented content.

Step 1: The Two-Minute Text-Layer Test

Before uploading an Arabic PDF to any AI summariser, run this quick test:

1. Open the PDF in a browser or desktop reader.
2. Select and copy a paragraph of Arabic text.
3. Paste the copied text into a plain text editor like Notepad.

Three outcomes are possible:

• Clean Arabic text: The characters paste cleanly in correct order. The file has an intact text layer, and AI models can process it directly.
• Nothing selectable: You cannot highlight text, or the page selects as one image. It is a scan.
• Disconnected letters, reversed order, or gibberish: Letters appear detached, words run backwards from left to right, or text pastes as symbols. This is a broken text layer. The AI may read that corrupted stream as real text and guess to fill the gaps.

To fix scanned or broken Arabic PDFs, choose one of two routes:

First, use Google Drive OCR. Upload the PDF to Google Drive and open it with Google Docs. Google Drive automatically detects languages, including Modern Standard Arabic, and extracts the text into a document. The file must be 2 MB or smaller, text at least 10 pixels high, right side up, and in common fonts. If your scan is larger than 2 MB, split the document into smaller parts before opening it with Google Docs.

Second, choose an AI tool that reads page images directly. ChatGPT says it analyses text and images in PDFs, including charts and diagrams. Claude analyses both text and visual elements, but its visual processing applies only to PDFs of 100 pages or fewer.

Step 2: Choose Your Tool

Select your platform based on vendor specifications:

Step 3: Summarise in Gemini Notebook

To summarise in Gemini Notebook and verify claims page by page, follow these steps:

1. Open notebook.google.com. Age verification in your Google Account is required before use; stricter policies apply to users under 18.
2. Create a new notebook.
3. Click Add sources and upload your Arabic PDF. Free users can include up to 50 sources, each up to 500,000 words or 200MB. Supported source types include PDF, Word (docx), txt, md, ePub, images, Google Docs/Slides, web URLs, audio, and public YouTube URLs.
4. Select specific sources in the Source panel to chat with just those files. If you load many sources, Gemini Notebook retrieves the most relevant parts first, so specific questions work better than broad commands.
5. Enter your summarisation prompt in the chat box. Gemini Notebook supports 80+ languages, including Arabic (Modern Standard) and Arabic (Colloquial Egyptian).
6. Click the citations in the generated response. Answers use direct quotes, text, and images from your sources as citations, jumping directly to the corresponding quote in your PDF.

Usage limits are compute-based; the quota refreshes every 5 hours until you reach your weekly limit. Quotas are 2x standard on Google AI Plus and 4x standard on Google AI Pro.

Step 4: The Prompt That Gets a Usable Summary

To prevent invented facts and secure a reliable summary, use this ready-to-copy prompt:

“Summarise the uploaded PDF section by section. For each section, provide a concise summary with the exact PDF page numbers where the information appears. Write the entire summary in Modern Standard Arabic [or state English if preferred]. Keep the length between 300 and 500 words. Following the summary, list separately: (1) all numbers, metrics, and percentages; (2) all dates; (3) all names of people, organisations, and locations. Keep all terms as in the source without translating or paraphrasing them. If any requested detail is not in the file, state plainly: ‘Information not in the file’—do not guess.”

Why each line is there:

• Summary by section with page numbers: Forces the model through the full document structure instead of skimming only the opening pages.
• Modern Standard Arabic: Establishes a standard formal register and prevents mixing regional dialects.
• Set length: Prevents vague overviews or incomplete outputs.
• List numbers, dates, and names separately: Isolating key data points makes quick verification possible and surfaces transcription errors.
• Keep terms as in the source: Preserves precise legal, administrative, and technical vocabulary without misleading synonyms.
• Say ‘not in the file’: Stops the model from guessing or hallucinating facts when information is missing.

Tip for Claude: Refer to pages by the PDF viewer’s page numbers, not the numbers printed on the page. For more on citation workflows, see our AI research workflow guide.

Step 5: Check the Summary in Five Minutes

Spend five minutes checking the summary before relying on it:

1. Check three claims: Pick three claims and open their citations or page numbers in the PDF to confirm the model preserved the original context.
2. Check every number and date: Review numbers against the source page. Look out for Hijri and Gregorian calendar mix-ups, a common trap in Arabic administrative documents that carry both. Verify that Western digits and Arabic-Indic digits were not transposed.
3. Check names of people and places: Ensure proper nouns were not altered due to missing or misplaced dots in the Arabic script.
4. Ask what was left out: Prompt the model with “What important details, conditions, or data did the summary leave out from the original file?” to reveal omitted points.

Long Files: Split Before Uploading

Manage long Arabic files according to vendor limits:

• Claude: Supports up to 500 MB per file, up to 20 files per chat, and PDFs up to 1,000 pages. But Claude analyses visuals only in PDFs of 100 pages or fewer; for PDFs from 101 to 1,000 pages, it processes text only. Split scanned books into 100-page parts so Claude can process the page images. Project files are limited to 30 MB with text extraction only (except multimodal PDFs).
• ChatGPT: Free users get 3 file uploads per day; paid accounts allow up to 80 files every 3 hours. Documents can reach 512 MB and 2 million tokens per file. Attach PDFs directly to chat rather than saving them as project files or GPT knowledge if they contain embedded images or scans.
• Gemini app: Accepts up to 10 files per prompt and 100 MB per non-video file. Google says a 1-million-token context window holds about 1,500 pages of text. There are rolling limits on chats with files that increase on Google AI Pro and Ultra.

Privacy and Data Handling

Do not upload confidential files to personal AI accounts.

Gemini Notebook states that uploaded data is not used to train Gemini Notebook unless you provide feedback. On Google Workspace and Google Workspace for Education accounts, uploaded data is not reviewed by human reviewers and is not used to train AI models.

Take your primary Arabic PDF, perform the two-minute copy-paste test to check its text layer, and upload the confirmed file to your chosen tool.