pdf-page-extract
Extract rich data from PDF pages including text spans with metadata, rendered PNG images, and page mapping. Creates persistent artifacts for downstream processing.
What this skill does
# PDF Page Extract Skill
## Purpose
This skill extracts all necessary data from PDF pages to enable accurate AI-driven HTML generation. It produces three critical artifacts:
1. **Rich extraction data** - Text spans with font metadata (sizes, styles, positions)
2. **Rendered PNG image** - Visual reference for AI to understand page layout
3. **Page mapping** - Authoritative mapping of PDF indices to book pages
This is the **deterministic, Python-based foundation** for the entire pipeline. All extracted data is saved to persistent files for traceability and future processing.
## What to Do
1. **Validate input parameters**
- Check PDF file exists and is readable
- Verify page range (PDF indices or book pages)
- Confirm output directory structure
2. **Establish page mapping** (if not already done)
- Run: `python3 Calypso/tools/read_page_footers.py`
- Scans page footers to establish PDF index → book page mapping
- Saves to: `analysis/page_mapping.json`
3. **Extract rich page data** using PyMuPDF and pdfplumber
- Run: `python3 Calypso/tools/rich_extractor.py`
- Extracts text spans with font metadata:
- Font name and size
- Bold/italic flags
- Position (bounding box)
- Color information
- Analyzes page structure to identify:
- Likely headings (by size and style)
- Paragraphs (regular text)
- Potential lists
- Detects tables using pdfplumber
- Saves to: `analysis/chapter_XX/rich_extraction.json`
4. **Render PDF page to PNG**
- Convert page to high-resolution PNG image (300+ DPI)
- Maintains visual fidelity for AI reference
- Saves to: `output/chapter_XX/page_artifacts/page_YY/02_page_XX.png`
5. **Extract embedded images** (if present)
- Run: `python3 Calypso/tools/extract_images.py`
- Extracts all images from page
- Saves: `output/chapter_XX/images/page_YY_image_*.png`
- Creates metadata: `page_YY_images.json`
6. **Validate extraction completeness**
- Verify all files saved correctly
- Check JSON files are valid
- Confirm PNG image is readable
- Validate page mapping consistency
## Input Parameters
```
chapter: <int> - Chapter number (1-8)
start_page: <int> - Starting PDF index (0-based) or page range
end_page: <int> - Ending PDF index (optional if single page)
pdf_path: <str> - Path to PDF file (default: Calypso/PREP-AL 4th Ed 9-26-25.pdf)
output_base: <str> - Output directory (default: Calypso/output)
mapping_file: <str> - Page mapping file (default: Calypso/analysis/page_mapping.json)
```
## Output Structure
### Artifact Files Saved
**Per-page artifacts** (in `output/chapter_XX/page_artifacts/page_YY/`):
- `01_rich_extraction.json` - Text spans with metadata
- `02_page_XX.png` - Rendered PDF page image
- `page_mapping.json` - Shared mapping file (symlink or copy)
**Extraction data** (in `analysis/chapter_XX/`):
- `rich_extraction.json` - Full extraction for all pages in chapter
- `page_6_pattern_analysis.json` - (Optional) Pattern analysis for specific pages
**Images** (in `output/chapter_XX/images/chapter_XX/`):
- `page_XX_image_*.png` - Embedded images from page
- `page_XX_images.json` - Metadata for embedded images
### Rich Extraction JSON Format
```json
{
"page_number": 16,
"pdf_index": 15,
"book_page": 17,
"chapter": 2,
"dimensions": {
"width": 612,
"height": 792
},
"text_spans": [
{
"text": "Rights in Real Estate",
"font": "Arial-BoldMT",
"size": 27.04,
"bold": true,
"italic": false,
"bbox": {
"x0": 72,
"y0": 150,
"x1": 400,
"y1": 177
},
"color": 0,
"sequence": 1
}
],
"analysis": {
"font_sizes": {
"27.04": 1,
"11.04": 45
},
"font_styles": {
"bold_27.04": 1,
"regular_11.04": 45
},
"likely_headings": [
{
"text": "Rights in Real Estate",
"level": 1,
"confidence": 0.95
}
],
"likely_paragraphs": [
{
"text": "Real property consists of...",
"type": "body_text"
}
]
},
"extraction_timestamp": "2025-11-08T14:30:00Z",
"extraction_tool": "rich_extractor.py v1.0"
}
```
## Python Commands to Execute
### Step 1: Establish Page Mapping
```bash
cd Calypso/tools
python3 read_page_footers.py \
--start 15 \
--end 28 \
--pdf "../PREP-AL 4th Ed 9-26-25.pdf" \
--output "../analysis/page_mapping.json"
```
**Success indicators:**
- Command exits with code 0
- Page mapping JSON created/updated
- All pages in range have entries
### Step 2: Extract Rich Data
```bash
cd Calypso/tools
python3 rich_extractor.py \
--pdf "../PREP-AL 4th Ed 9-26-25.pdf" \
--start 15 \
--end 28 \
--output "../analysis/chapter_02/rich_extraction.json"
```
**Success indicators:**
- Command exits with code 0
- JSON file created
- File contains text_spans array
- All pages in range represented
### Step 3: Render to PNG
```bash
cd Calypso/tools
python3 -c "
import fitz
pdf = fitz.open('../PREP-AL 4th Ed 9-26-25.pdf')
for page_idx in range(15, 29):
page = pdf[page_idx]
pix = page.get_pixmap(matrix=fitz.Matrix(3, 3)) # 300% zoom for high-res
pix.save(f'../output/chapter_02/page_artifacts/page_{page_idx:02d}/02_page_{page_idx}.png')
pdf.close()
"
```
### Step 4: Extract Images (if present)
```bash
cd Calypso/tools
# For each page with images
python3 extract_images.py \
--page 17 \
--pdf "../PREP-AL 4th Ed 9-26-25.pdf" \
--output "../output" \
--mapping "../analysis/page_mapping.json"
```
## Quality Checks
Before declaring extraction complete:
1. **File existence**
- [ ] `01_rich_extraction.json` exists
- [ ] `02_page_XX.png` exists and is valid
- [ ] `page_mapping.json` exists
2. **JSON validity**
- [ ] JSON files parse without errors
- [ ] All required fields present
- [ ] No null/undefined values in critical fields
3. **Data completeness**
- [ ] All pages in range have text_spans
- [ ] Text content is not empty
- [ ] Font sizes are reasonable (> 0)
- [ ] Bounding boxes are within page dimensions
4. **Image quality**
- [ ] PNG files are readable
- [ ] Image dimensions match PDF page size
- [ ] No corrupted or blank images
## Error Handling
**If PDF file not found:**
- Exit with error message
- Do not create partial artifacts
**If page mapping fails:**
- Fall back to default indexing (PDF index = book page - 1)
- Log warning
- Continue extraction
**If rich extraction produces no text:**
- Check if page is image-only
- Mark in metadata: `"page_type": "image_only"`
- Continue (ASCII preview will handle image OCR)
**If PNG rendering fails:**
- Use fallback: save raw PDF page as PDF image
- Log warning
- Continue to next step
## Persistence & Traceability
All artifacts include metadata:
- Extraction timestamp
- Tool version
- Input parameters
- Processing status
This enables:
- Reproducibility (re-extract with same parameters)
- Debugging (trace what data was extracted)
- Auditing (track all changes to artifacts)
- Caching (skip re-extraction if unchanged)
## Success Criteria
✓ All required files created in correct directories
✓ Rich extraction JSON is valid and complete
✓ PNG image renders correctly
✓ Page mapping is accurate
✓ All data persisted and ready for next skill
✓ No extraction errors or warnings
## Next Steps
Once extraction completes successfully:
1. **Skill 2** will create ASCII preview from extracted data
2. **Skill 3** will use extraction + PNG + ASCII for HTML generation
3. All artifacts available for validation and debugging
## Troubleshooting
**PDF won't open**: Verify file path, ensure PDF is not corrupted
**No text extracted**: Page may be image-only (OCR needed)
**Wrong page numbers**: Check page_mapping.json for accuracy
**PNG images are blank**: Try increasing zoom factor (3x = 300 DPI)
## Implementation Notes
- This skill is **fully deterministic** - same inputs always producRelated in Writing & Docs
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