PDF Vision Extraction Skill (Enhanced)

Overview

This skill handles image-based or scanned PDFs that contain no selectable text. It supports multiple vision APIs with automatic fallback:

Primary Models

• - Xflow: qwen3-vl-plus (your primary vision model)
• ZhipuAI: glm-4.6v-flash (free vision model with fallback support)
• Fallback: glm-5 (text-only, but may work with some image prompts)

Unlike traditional PDF text extraction tools (pdftotext, pdfplumber) which only work on text-based PDFs, this skill can process:

• - Scanned documents
• Image-only PDFs
• Photographed documents
• Handwritten notes (with limitations)
• Complex layouts with tables and formatting

Supported Models

Vision-Capable Models

Provider	Model	Type	Context	Free
Xflow	INLINECODE5	Vision + Text	131K	❌
ZhipuAI

glm-4.6v-flash | Vision + Text | 32K | ✅ |

Additional Text Models (for fallback)

Provider	Model	Context	Free
ZhipuAI	INLINECODE8	128K	✅
ZhipuAI

cogview-3-flash | 32K | ✅ |

*Note: glm-5 is primarily text-only but may handle image prompts in some cases.

Prerequisites

1. API Configuration

Xflow Configuration (already set up):

• - models.providers.openai.baseUrl: INLINECODE12
• INLINECODE13: Your Xflow API key

ZhipuAI Configuration (update token):

• - models.providers.zhipuai.baseUrl: INLINECODE15
• INLINECODE16: Your ZhipuAI API token

2. Required System Tools

• - pypdfium2 Python library (for PDF to image conversion)
• INLINECODE18 (for API calls)
• INLINECODE19 (for image encoding)

3. Python Libraries (already installed)

Usage

Automatic Fallback Mode (Default)

Specific Model Selection

Structured Data Extraction

Multi-page PDF Handling

Configuration

Environment Variables

• - models.providers.openai.baseUrl & INLINECODE22
• INLINECODE23 & INLINECODE24

Output Format

Examples

Cost-Optimized Extraction (Free Model)

High-Quality Extraction (Premium Model)

Automatic Fallback (Recommended)

Model Comparison

GLM-4.6V-Flash (Free)

• - ✅ Completely free
• ✅ Good Chinese text recognition
• ✅ Decent table structure preservation
• ⚠️ Lower context window (32K vs 131K)
• ⚠️ May struggle with very complex layouts

Qwen3-VL-Plus (Premium)

• - ✅ Superior image understanding
• ✅ Excellent table and structure recognition
• ✅ Larger context window (131K)
• ✅ Better handling of mixed languages
• ❌ Requires paid API access

Limitations

• - Single page processing: Currently processes one page at a time
• Image quality: Better results with higher resolution scans
• Complex layouts: May struggle with very dense or overlapping text
• Handwriting: Limited accuracy with handwritten content
• File size: Large PDFs may exceed API token limits

Technical Implementation

The skill follows this workflow:

1. 1. PDF to Image: Converts specified PDF page to PNG using INLINECODE28
2. Model Selection: Chooses model based on user preference or fallback logic
3. API Call: Sends image + prompt to selected vision API endpoint
4. Response Parsing: Extracts and returns the AI-generated text content
5. Fallback: If primary model fails, tries alternative models

For debugging, temporary files are created in /tmp/:

• - /tmp/pdf_vision_page.png - converted image
• INLINECODE31 - API request payload
• INLINECODE32 - API response

Integration Notes

This skill complements the standard pdf skill:

• - Use pdf skill for text-based PDFs (faster, no API cost)
• Use pdf-vision skill for image-based/scanned PDFs (requires vision API)

Both skills can be used together in a fallback pattern:

1. 1. Try pdf skill first
2. If no text extracted, fall back to pdf-vision skill

Cost Optimization Tips

1. 1. Use GLM-4.6V-Flash for routine tasks - it's free and quite capable
2. Reserve Qwen3-VL-Plus for complex documents - when you need maximum accuracy
3. Test both models on your document types - choose based on your quality requirements
4. Monitor API usage - track which models you're using most

Update Your GLM API Token

Replace the placeholder token in your config:
CODEBLOCK5