AVAILABLE FOR WEB, FLUTTER & QA PROJECTS
How to use this tool
1. Specify PDF Page Count
Enter total pages across single or multiple PDF documents.
2. Choose Page Content Density
Select density preset: Dense Text / Academic (500-600 words/page), Standard Business Report (300-400 words/page), or Sparse Presentation / Slides (80-150 words/page).
3. Configure Target Chunk Size & Overlap
Choose target chunk token size (e.g. 512 tokens) and overlap percentage.
4. Inspect Chunks & Embedding Bills
Review estimated total extracted words, token volume, chunk counts, and OpenAI embedding costs.
Formula or logic used
PDF Text Extraction & Vectorization Math
PDF pages vary widely in text density. Extraction estimates convert pages to word counts, apply token multipliers, and divide into overlapping chunks.
Estimated Total Words: $W_{\text{total}} = \text{Pages} \times \text{Words per Page}$Estimated Total Tokens: $T_{\text{total}} = W_{\text{total}} \times 1.33$ (standard English tokenization ratio)Stride Size: $S = \text{Chunk Size} \times (1 - \frac{\text{Overlap \%}}{100})$Total Generated Chunks: $N = \max(1, \lceil \frac{T_{\text{total}}}{S} \rceil)$Embedding Cost = $\frac{N \times \text{Chunk Size}}{10^6} \times P_{\text{embedding}}$
Examples
Example 1: Enterprise Annual Financial Report (120 pages)
Quick, accurate sizing for parsing and embedding corporate 10-K filings into vector search.
Example 2: Academic Research Paper Archive (1,500 pages)
Estimates vector count and indexing duration for large scientific literature corpora.
Common use cases
Document Processing Pipeline Sizing
Estimate serverless timeout limits and batch sizes when running PDF text extractors (pypdf, pdfplumber, LlamaParse).
Enterprise Knowledge Base Ingestion
Budget total vector database records before uploading thousands of internal employee handbooks.
Contract Analysis Quoting
Quote accurate turnaround timelines and infrastructure costs for legal tech RAG platforms.
OCR Cost Estimation
Determine how much third-party vision OCR APIs (e.g. AWS Textract, Google Document AI) will cost per page.
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Frequently asked questions
How many words are on a typical PDF page?
A standard single-spaced business PDF page contains roughly 300 to 450 words. Dense academic papers with two columns contain 500 to 700 words. Slide decks and presentations typically have 50 to 120 words.
How do tables and diagrams in PDFs affect chunking?
Standard text extraction often mangles tabular data. For PDFs with complex tables, use specialized parsers (like LlamaParse or unstructured) that convert tables into Markdown or HTML tables before chunking.
Why do scanned PDFs require different processing?
Scanned PDFs contain raw images rather than text streams. They must first pass through Optical Character Recognition (OCR) before any words or tokens can be extracted.
Should each PDF page be a separate chunk?
Rarely. Sentences and paragraphs frequently cross page boundaries. It is much better to concatenate the entire document's text stream and apply standard semantic or recursive character chunking with overlap.
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