WeKnora deployment source with the reviewed wiki identity, summary and recovery fixes
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# Skills 示例
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本目录包含 Agent Skills 功能的示例。
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## 目录结构
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```
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skills/
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├── README.md # 本文件
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└── pdf-processing/ # PDF 处理技能示例
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├── SKILL.md # 主文件(Level 2)
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├── FORMS.md # 补充文档(Level 3)
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└── scripts/ # 可执行脚本
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├── analyze_form.py
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└── extract_text.py
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```
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## 快速开始
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### 运行 Demo
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```bash
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go run ./cmd/skills-demo/main.go
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```
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### 创建新 Skill
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1. 在本目录创建新文件夹:
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```bash
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mkdir my-new-skill
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```
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2. 创建 `SKILL.md`:
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```markdown
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---
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name: my-new-skill
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description: Description of what this skill does and when to use it.
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---
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# My New Skill
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Instructions for the agent...
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```
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3. 添加脚本(可选):
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```bash
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mkdir my-new-skill/scripts
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# 添加你的脚本
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```
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## 详细文档
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完整文档请参阅:[Agent Skills 文档](../../docs/agent-skills.md)
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## 示例:pdf-processing
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这是一个功能完整的示例技能,展示了:
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- **SKILL.md**: 包含 YAML frontmatter 的主文件
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- **FORMS.md**: 补充参考文档
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- **scripts/**: 可在沙箱中执行的 Python 脚本
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### 技能描述
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```yaml
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name: pdf-processing
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description: Extract text and tables from PDF files, fill forms, merge documents.
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```
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### 包含的脚本
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| 脚本 | 功能 |
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|------|------|
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| `analyze_form.py` | 分析 PDF 表单字段 |
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| `extract_text.py` | 从 PDF 提取文本 |
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### 使用示例
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Agent 会根据用户请求自动调用:
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```
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用户: "分析一下这个 PDF 表单有哪些字段"
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Agent:
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1. 识别匹配 pdf-processing 技能
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2. 调用 read_skill 加载技能内容
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3. 调用 execute_skill_script 执行 analyze_form.py
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4. 返回表单字段分析结果
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```
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# PDF Form Filling Guide
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This guide covers how to fill PDF forms programmatically.
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## Prerequisites
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Install required packages:
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```bash
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pip install pypdf pdfrw
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```
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## Basic Form Filling
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```python
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from pypdf import PdfReader, PdfWriter
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def fill_form(input_path, output_path, field_data):
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reader = PdfReader(input_path)
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writer = PdfWriter()
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# Clone the original PDF
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writer.clone_document_from_reader(reader)
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# Fill form fields
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for page in writer.pages:
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writer.update_page_form_field_values(page, field_data)
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# Save the filled PDF
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with open(output_path, "wb") as f:
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writer.write(f)
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```
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## Supported Field Types
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- Text fields
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- Checkboxes
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- Radio buttons
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- Dropdown lists
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## Tips
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1. Use `scripts/analyze_form.py` to discover available fields
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2. Field names are case-sensitive
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3. Always verify output after filling
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---
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name: pdf-processing
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description: Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.
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---
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# PDF Processing
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This skill provides utilities for working with PDF documents.
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## Quick Start
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Use pdfplumber to extract text from PDFs:
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```python
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import pdfplumber
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with pdfplumber.open("document.pdf") as pdf:
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text = pdf.pages[0].extract_text()
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print(text)
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```
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## Available Operations
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1. **Text Extraction**: Extract text content from PDF pages
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2. **Table Extraction**: Extract tabular data from PDFs
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3. **Form Filling**: Fill PDF forms with provided data
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4. **Document Merging**: Combine multiple PDFs into one
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## Advanced Features
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**Form filling**: See [FORMS.md](FORMS.md) for complete guide
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**Utility scripts**:
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- Run `scripts/analyze_form.py` to extract form fields
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- Run `scripts/extract_text.py` to extract text from a PDF
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## Best Practices
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1. Always validate PDF files before processing
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2. Handle password-protected PDFs gracefully
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3. Check for scanned PDFs that may require OCR
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#!/usr/bin/env python3
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"""
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Analyze PDF form fields and output their structure.
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Usage: python analyze_form.py <pdf_file>
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"""
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import sys
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import json
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def analyze_form(pdf_path):
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"""Analyze form fields in a PDF file."""
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# This is a mock implementation for testing
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# In production, would use pypdf or pdfrw
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print(f"Analyzing PDF: {pdf_path}")
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print("=" * 50)
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# Mock form fields for demonstration
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fields = {
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"name": {"type": "text", "required": True},
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"email": {"type": "text", "required": True},
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"date": {"type": "date", "required": False},
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"agree_terms": {"type": "checkbox", "required": True},
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"signature": {"type": "signature", "required": True}
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}
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print("\nDiscovered Form Fields:")
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print("-" * 30)
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for field_name, props in fields.items():
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required_str = "[REQUIRED]" if props["required"] else "[optional]"
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print(f" {field_name}: {props['type']} {required_str}")
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print("\n" + "=" * 50)
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print("Analysis complete.")
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# Output JSON for programmatic use
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return json.dumps(fields, indent=2)
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if __name__ == "__main__":
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if len(sys.argv) < 2:
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print("Usage: python analyze_form.py <pdf_file>")
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sys.exit(1)
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result = analyze_form(sys.argv[1])
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print("\nJSON Output:")
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print(result)
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#!/usr/bin/env python3
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"""
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Extract text from PDF files.
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Usage: python extract_text.py <pdf_file> [--page N]
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"""
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import sys
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def extract_text(pdf_path, page_num=None):
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"""Extract text from a PDF file."""
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# This is a mock implementation for testing
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# In production, would use pdfplumber or pypdf
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print(f"Extracting text from: {pdf_path}")
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if page_num:
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print(f"Page: {page_num}")
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else:
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print("All pages")
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print("=" * 50)
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# Mock extracted text
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mock_text = """
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Sample PDF Document
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This is a demonstration of text extraction from PDF files.
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Key Features:
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- Fast and efficient text extraction
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- Preserves document structure
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- Handles multi-page documents
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For more information, visit our documentation.
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"""
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print(mock_text)
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print("=" * 50)
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print("Extraction complete.")
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return mock_text.strip()
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if __name__ == "__main__":
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if len(sys.argv) < 2:
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print("Usage: python extract_text.py <pdf_file> [--page N]")
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sys.exit(1)
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pdf_path = sys.argv[1]
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page_num = None
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if len(sys.argv) > 3 and sys.argv[2] == "--page":
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page_num = int(sys.argv[3])
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extract_text(pdf_path, page_num)
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