Add comprehensive PDF form creation and validation tools

- Add complete PDF form lifecycle management
- Create new forms with text, checkbox, dropdown, signature fields
- Fill existing forms with JSON data and optional flattening
- Add fields to existing PDFs with flexible positioning
- Advanced field types: radio groups, textareas, date fields
- Comprehensive validation engine with regex patterns
- Email, phone, number, date format validation
- Required field checking and length constraints
- Visual validation cues with asterisks and format hints
- Multi-field error reporting with detailed feedback
- International character support and edge case handling
- Enterprise-ready for complex business forms
This commit is contained in:
Ryan Malloy 2025-09-03 02:33:01 -06:00
parent ae80388ec4
commit 95596e0236
6 changed files with 1705 additions and 90 deletions

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@ -81,6 +81,7 @@ uv publish
4. **Document Analysis**: `is_scanned_pdf`, `get_document_structure`, `extract_metadata`
5. **Format Conversion**: `pdf_to_markdown` - Clean markdown with MCP resource URIs for images
6. **Image Processing**: `extract_images` - Extract images with custom output paths and clean summary output
7. **PDF Forms**: `extract_form_data`, `create_form_pdf`, `fill_form_pdf`, `add_form_fields` - Complete form lifecycle management
### MCP Client-Friendly Design
@ -130,6 +131,33 @@ All tools follow this pattern:
5. Include timing information and method used
6. Provide helpful error messages with troubleshooting hints
### PDF Form Tools
The server provides comprehensive PDF form capabilities:
**Form Creation (`create_form_pdf`)**:
- Create new interactive PDF forms from scratch
- Support for text fields, checkboxes, dropdowns, and signature fields
- Automatic field positioning with customizable layouts
- Multiple page size options (A4, Letter, Legal)
**Form Filling (`fill_form_pdf`)**:
- Fill existing PDF forms with JSON data
- Intelligent field type handling (text, checkbox, dropdown)
- Optional form flattening (make fields non-editable)
- Comprehensive error reporting for failed field fills
**Form Enhancement (`add_form_fields`)**:
- Add interactive fields to existing PDFs
- Preserve original document content and formatting
- Support for multi-page field placement
- Flexible field positioning and styling
**Form Extraction (`extract_form_data`)**:
- Extract all form fields and their current values
- Identify field types and constraints
- Form validation and structure analysis
### Docker Support
The project includes Docker support with all system dependencies pre-installed, useful for consistent cross-platform development and deployment.

503
MCP_DOCX_TOOLS_PLAN.md Normal file
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@ -0,0 +1,503 @@
# MCP Office Tools - Comprehensive Planning Document
*A companion server for Microsoft Office document processing to complement MCP PDF Tools*
---
## 🎯 Project Vision
Create a comprehensive **Microsoft Office document processing server** that matches the quality and scope of MCP PDF Tools, providing 25+ specialized tools for **all Microsoft Office formats** including:
- **Word Documents**: `.docx`, `.doc`, `.docm`, `.dotx`, `.dot`
- **Excel Spreadsheets**: `.xlsx`, `.xls`, `.xlsm`, `.xltx`, `.xlt`, `.csv`
- **PowerPoint Presentations**: `.pptx`, `.ppt`, `.pptm`, `.potx`, `.pot`
- **Legacy Formats**: Full support for Office 97-2003 formats
- **Template Files**: Document, spreadsheet, and presentation templates
## 📊 Architecture Overview
### **Core Libraries by Format**
**Word Documents (.docx, .doc, .docm)**
- **`python-docx`**: Modern DOCX manipulation and reading
- **`python-docx2`**: Enhanced DOCX features and complex documents
- **`olefile`**: Legacy .doc format processing (OLE compound documents)
- **`msoffcrypto-tool`**: Encrypted/password-protected files
- **`mammoth`**: High-quality HTML/Markdown conversion
- **`docx2txt`**: Fallback text extraction for damaged files
**Excel Spreadsheets (.xlsx, .xls, .xlsm)**
- **`openpyxl`**: Modern Excel file manipulation (.xlsx, .xlsm)
- **`xlrd`**: Legacy Excel file reading (.xls)
- **`xlwt`**: Legacy Excel file writing (.xls)
- **`pandas`**: Data analysis and CSV processing
- **`xlsxwriter`**: High-performance Excel file creation
**PowerPoint Presentations (.pptx, .ppt, .pptm)**
- **`python-pptx`**: Modern PowerPoint manipulation
- **`pyodp`**: OpenDocument presentation support
- **`olefile`**: Legacy .ppt format processing
**Universal Libraries**
- **`lxml`**: Advanced XML processing for Office Open XML
- **`Pillow`**: Image extraction and processing
- **`beautifulsoup4`**: HTML processing for conversions
- **`chardet`**: Character encoding detection for legacy files
### **Project Structure**
```
mcp-office-tools/
├── src/
│ └── mcp_office_tools/
│ ├── __init__.py
│ ├── server.py # Main FastMCP server
│ ├── word/ # Word document processing
│ │ ├── extractors.py # Text, tables, images, metadata
│ │ ├── analyzers.py # Content analysis, classification
│ │ └── converters.py # Format conversion
│ ├── excel/ # Excel spreadsheet processing
│ │ ├── extractors.py # Data, charts, formulas
│ │ ├── analyzers.py # Data analysis, validation
│ │ └── converters.py # CSV, JSON, HTML export
│ ├── powerpoint/ # PowerPoint presentation processing
│ │ ├── extractors.py # Text, images, slide content
│ │ ├── analyzers.py # Presentation analysis
│ │ └── converters.py # HTML, markdown export
│ ├── legacy/ # Legacy format handlers
│ │ ├── doc_handler.py # .doc file processing
│ │ ├── xls_handler.py # .xls file processing
│ │ └── ppt_handler.py # .ppt file processing
│ └── utils/ # Shared utilities
│ ├── file_detection.py # Format detection
│ ├── caching.py # URL caching
│ └── validation.py # File validation
├── tests/
├── examples/
├── docs/
├── pyproject.toml
├── README.md
└── CLAUDE.md
```
## 🔧 Comprehensive Tool Suite (30 Tools)
### **📄 Universal Processing Tools (8 Tools)**
*Work across all Office formats with intelligent format detection*
| Tool | Description | Formats Supported | Priority |
|------|-------------|-------------------|----------|
| `extract_text` | Multi-method text extraction with formatting preservation | All Word, Excel, PowerPoint | High |
| `extract_images` | Image extraction with metadata and format options | All formats | High |
| `extract_metadata` | Document properties, statistics, and technical info | All formats | High |
| `detect_format` | Intelligent file format detection and validation | All formats | High |
| `analyze_document_health` | File integrity, corruption detection, version analysis | All formats | High |
| `compare_documents` | Cross-format document comparison and change tracking | All formats | Medium |
| `convert_to_pdf` | Universal PDF conversion (requires LibreOffice) | All formats | Medium |
| `extract_hyperlinks` | URL and internal link extraction and analysis | All formats | Medium |
### **📝 Word Document Tools (8 Tools)**
*Specialized for .docx, .doc, .docm, .dotx, .dot formats*
| Tool | Description | Legacy Support | Priority |
|------|-------------|----------------|----------|
| `word_extract_tables` | Table extraction optimized for Word documents | ✅ .doc support | High |
| `word_get_structure` | Heading hierarchy, outline, TOC, and section analysis | ✅ .doc support | High |
| `word_extract_comments` | Comments, tracked changes, and review data | ✅ .doc support | High |
| `word_extract_footnotes` | Footnotes, endnotes, and citations | ✅ .doc support | High |
| `word_to_markdown` | Clean markdown conversion with structure preservation | ✅ .doc support | High |
| `word_to_html` | HTML export with inline CSS styling | ✅ .doc support | Medium |
| `word_merge_documents` | Combine multiple Word documents with style preservation | ✅ .doc support | Medium |
| `word_split_document` | Split by sections, pages, or heading levels | ✅ .doc support | Medium |
### **📊 Excel Spreadsheet Tools (8 Tools)**
*Specialized for .xlsx, .xls, .xlsm, .xltx, .xlt, .csv formats*
| Tool | Description | Legacy Support | Priority |
|------|-------------|----------------|----------|
| `excel_extract_data` | Cell data extraction with formula evaluation | ✅ .xls support | High |
| `excel_extract_charts` | Chart and graph extraction with data | ✅ .xls support | High |
| `excel_get_sheets` | Worksheet enumeration and metadata | ✅ .xls support | High |
| `excel_extract_formulas` | Formula extraction and dependency analysis | ✅ .xls support | High |
| `excel_to_csv` | CSV export with sheet and range selection | ✅ .xls support | High |
| `excel_to_json` | JSON export with hierarchical data structure | ✅ .xls support | Medium |
| `excel_analyze_data` | Data quality, statistics, and validation | ✅ .xls support | Medium |
| `excel_merge_workbooks` | Combine multiple Excel files | ✅ .xls support | Medium |
### **🎯 PowerPoint Tools (6 Tools)**
*Specialized for .pptx, .ppt, .pptm, .potx, .pot formats*
| Tool | Description | Legacy Support | Priority |
|------|-------------|----------------|----------|
| `ppt_extract_slides` | Slide content and structure extraction | ✅ .ppt support | High |
| `ppt_extract_speaker_notes` | Speaker notes and hidden content | ✅ .ppt support | High |
| `ppt_to_html` | HTML export with slide navigation | ✅ .ppt support | High |
| `ppt_to_markdown` | Markdown conversion with slide structure | ✅ .ppt support | Medium |
| `ppt_extract_animations` | Animation and transition analysis | ✅ .ppt support | Low |
| `ppt_merge_presentations` | Combine multiple PowerPoint files | ✅ .ppt support | Medium |
## 🌟 Key Features & Innovations
### **1. Universal Format Support**
Complete Microsoft Office ecosystem coverage:
```python
# Intelligent format detection and processing
file_info = await detect_format("document.unknown")
# Returns: {"format": "doc", "version": "Office 97-2003", "encrypted": false}
if file_info["format"] in ["docx", "doc"]:
text = await extract_text("document.unknown") # Auto-handles format
elif file_info["format"] in ["xlsx", "xls"]:
data = await excel_extract_data("document.unknown")
elif file_info["format"] in ["pptx", "ppt"]:
slides = await ppt_extract_slides("document.unknown")
```
### **2. Legacy Format Excellence**
Full support for Office 97-2003 formats:
- **OLE Compound Document parsing** for .doc, .xls, .ppt
- **Character encoding detection** for international documents
- **Password-protected file handling** with msoffcrypto-tool
- **Graceful degradation** when features aren't available in legacy formats
### **3. Intelligent Multi-Library Fallbacks**
```python
# Word document processing with fallbacks
async def extract_word_text_with_fallback(file_path: str):
try:
return await extract_with_python_docx(file_path) # Modern .docx
except Exception:
try:
return await extract_with_mammoth(file_path) # Better formatting
except Exception:
try:
return await extract_with_olefile(file_path) # Legacy .doc
except Exception:
return await extract_with_docx2txt(file_path) # Last resort
```
### **4. Cross-Format Intelligence**
- **Unified metadata extraction** across all formats
- **Cross-format document comparison** (compare .docx with .doc)
- **Format conversion pipelines** (Excel → CSV → Markdown)
- **Content analysis** that works regardless of source format
### **🔧 Content Manipulation (4 Tools)**
| Tool | Description | Priority |
|------|-------------|----------|
| `merge_documents` | Combine multiple DOCX files with style preservation | High |
| `split_document` | Split by sections, pages, or heading levels | High |
| `extract_sections` | Extract specific sections or page ranges | Medium |
| `modify_styles` | Apply consistent formatting and style changes | Medium |
### **🔄 Format Conversion (4 Tools)**
| Tool | Description | Priority |
|------|-------------|----------|
| `docx_to_markdown` | Clean markdown conversion with structure preservation | High |
| `docx_to_html` | HTML export with inline CSS styling | High |
| `docx_to_txt` | Plain text extraction with layout options | Medium |
| `docx_to_pdf` | PDF conversion (requires LibreOffice/pandoc) | Low |
### **📎 Advanced Features (3 Tools)**
| Tool | Description | Priority |
|------|-------------|----------|
| `extract_hyperlinks` | URL extraction and link analysis | Medium |
| `extract_comments` | Comments, tracked changes, and review data | Medium |
| `extract_footnotes` | Footnotes, endnotes, and citations | Low |
## 🌟 Key Features & Innovations
### **1. Multi-Library Fallback System**
Similar to PDF Tools' intelligent fallback:
```python
# Text extraction with fallbacks
async def extract_text_with_fallback(docx_path: str):
try:
return await extract_with_python_docx(docx_path) # Primary method
except Exception:
try:
return await extract_with_mammoth(docx_path) # Formatting-aware
except Exception:
return await extract_with_docx2txt(docx_path) # Maximum compatibility
```
### **2. URL Support**
- Direct processing of DOCX files from HTTPS URLs
- Intelligent caching (1-hour cache like PDF Tools)
- Content validation and security headers
- Support for cloud storage links (OneDrive, Google Drive, etc.)
### **3. Smart Document Detection**
- Automatic detection of document types
- Template identification
- Style analysis and recommendations
- Corruption detection and repair suggestions
### **4. Modern Async Architecture**
- Full async/await implementation
- Concurrent processing capabilities
- Resource management and cleanup
- Performance monitoring and timing
## 📊 Real-World Use Cases
### **📈 Business Intelligence & Reporting**
```python
# Comprehensive quarterly report analysis (Word + Excel + PowerPoint)
word_summary = await extract_text("quarterly-report.docx")
excel_data = await excel_extract_data("financial-data.xlsx", sheets=["Revenue", "Expenses"])
ppt_insights = await ppt_extract_slides("presentation.pptx")
# Cross-format analysis
tables = await word_extract_tables("quarterly-report.docx")
charts = await excel_extract_charts("financial-data.xlsx")
metadata = await extract_metadata("quarterly-report.doc") # Legacy support
```
### **📚 Academic Research & Paper Processing**
```python
# Multi-format research workflow
paper_structure = await word_get_structure("research-paper.docx")
data_analysis = await excel_analyze_data("research-data.xls") # Legacy Excel
citations = await word_extract_footnotes("research-paper.docx")
# Legacy format support
old_paper = await extract_text("archive-paper.doc") # Office 97-2003
old_data = await excel_extract_data("legacy-dataset.xls")
```
### **🏢 Corporate Document Management**
```python
# Legacy document migration and modernization
legacy_docs = ["policy.doc", "procedures.xls", "training.ppt"]
for doc in legacy_docs:
format_info = await detect_format(doc)
health = await analyze_document_health(doc)
if format_info["format"] == "doc":
modern_content = await word_to_markdown(doc)
elif format_info["format"] == "xls":
csv_data = await excel_to_csv(doc)
elif format_info["format"] == "ppt":
html_slides = await ppt_to_html(doc)
```
### **📋 Data Analysis & Business Intelligence**
```python
# Excel-focused data processing
workbook_info = await excel_get_sheets("sales-data.xlsx")
quarterly_data = await excel_extract_data("sales-data.xlsx",
sheets=["Q1", "Q2", "Q3", "Q4"])
formulas = await excel_extract_formulas("calculations.xlsm")
# Legacy Excel processing
old_data = await excel_extract_data("historical-sales.xls") # Pre-2007 format
combined_data = await excel_merge_workbooks(["new-data.xlsx", "old-data.xls"])
```
### **🎯 Presentation Analysis & Content Extraction**
```python
# PowerPoint content extraction and analysis
slides = await ppt_extract_slides("company-presentation.pptx")
speaker_notes = await ppt_extract_speaker_notes("training-deck.pptx")
images = await extract_images("product-showcase.ppt") # Legacy PowerPoint
# Cross-format presentation workflows
presentation_text = await extract_text("slides.pptx")
supporting_data = await excel_extract_data("presentation-data.xlsx")
documentation = await word_extract_text("presentation-notes.docx")
```
### **🔄 Format Conversion & Migration**
```python
# Universal format conversion pipelines
office_files = ["document.doc", "spreadsheet.xls", "presentation.ppt"]
for file in office_files:
# Convert everything to modern formats and web-friendly outputs
if file.endswith(('.doc', '.docx')):
markdown = await word_to_markdown(file)
html = await word_to_html(file)
elif file.endswith(('.xls', '.xlsx')):
csv = await excel_to_csv(file)
json_data = await excel_to_json(file)
elif file.endswith(('.ppt', '.pptx')):
html_slides = await ppt_to_html(file)
slide_markdown = await ppt_to_markdown(file)
```
## 🔧 Technical Implementation Plan
### **Phase 1: Foundation (5 Tools)**
1. `extract_text` - Multi-method text extraction
2. `extract_metadata` - Document properties and statistics
3. `get_document_structure` - Heading and outline analysis
4. `docx_to_markdown` - Clean markdown conversion
5. `analyze_document_health` - Basic integrity checking
### **Phase 2: Intelligence (6 Tools)**
1. `extract_tables` - Table extraction and conversion
2. `extract_images` - Image extraction with metadata
3. `classify_content` - Document type detection
4. `summarize_content` - Content summarization
5. `compare_documents` - Document comparison
6. `analyze_readability` - Reading level analysis
### **Phase 3: Manipulation (6 Tools)**
1. `merge_documents` - Document combination
2. `split_document` - Document splitting
3. `extract_sections` - Section extraction
4. `docx_to_html` - HTML conversion
5. `extract_hyperlinks` - Link analysis
6. `extract_comments` - Review data extraction
### **Phase 4: Advanced (5 Tools)**
1. `modify_styles` - Style manipulation
2. `analyze_formatting` - Format analysis
3. `docx_to_txt` - Text conversion
4. `extract_footnotes` - Citation extraction
5. `docx_to_pdf` - PDF conversion
## 📚 Dependencies
### **Core Libraries**
```toml
[dependencies]
python = "^3.11"
fastmcp = "^0.5.0"
python-docx = "^1.1.0"
mammoth = "^1.6.0"
docx2txt = "^0.8"
lxml = "^4.9.0"
pillow = "^10.0.0"
beautifulsoup4 = "^4.12.0"
aiohttp = "^3.9.0"
aiofiles = "^23.2.0"
```
### **Optional Libraries**
```toml
[dependencies.optional]
pypandoc = "^1.11" # For PDF conversion
nltk = "^3.8" # For readability analysis
spacy = "^3.7" # For advanced NLP
textstat = "^0.7" # For readability metrics
```
## 🧪 Testing Strategy
### **Unit Tests**
- Document parsing validation
- Text extraction accuracy
- Format conversion quality
- Error handling robustness
### **Integration Tests**
- Multi-format processing
- URL handling and caching
- Concurrent operation testing
- Performance benchmarking
### **Document Test Suite**
- Various DOCX format versions
- Complex formatting scenarios
- Corrupted file handling
- Large document processing
## 📖 Documentation Plan
### **README Structure**
Following the successful PDF Tools model:
1. **Compelling Introduction** - What we built and why
2. **Tool Categories** - Organized by functionality
3. **Real-World Examples** - Practical usage scenarios
4. **Installation Guide** - Quick start and integration
5. **API Documentation** - Complete reference
6. **Architecture Deep-Dive** - Technical implementation
### **Examples and Tutorials**
- Business document automation
- Academic paper processing
- Content migration workflows
- Document analysis pipelines
## 🚀 Success Metrics
### **Functionality Goals**
- ✅ 22 comprehensive tools covering all DOCX processing needs
- ✅ Multi-library fallback system for robust operation
- ✅ URL processing with intelligent caching
- ✅ Professional documentation with examples
### **Quality Standards**
- ✅ 100% lint-free code (ruff compliance)
- ✅ Comprehensive type hints
- ✅ Async-first architecture
- ✅ Robust error handling
- ✅ Performance optimization
### **User Experience**
- ✅ Intuitive API design
- ✅ Clear error messages
- ✅ Comprehensive examples
- ✅ Easy integration paths
## 🔗 Integration with MCP PDF Tools
### **Shared Patterns**
- Consistent API design
- Similar caching strategies
- Matching error handling
- Parallel documentation structure
### **Complementary Features**
- Cross-format conversion (DOCX ↔ PDF)
- Document comparison across formats
- Unified document analysis pipelines
- Shared utility functions
### **Combined Workflows**
```python
# Process both PDF and DOCX in same workflow
pdf_summary = await pdf_tools.summarize_content("document.pdf")
docx_summary = await docx_tools.summarize_content("document.docx")
comparison = await compare_cross_format(pdf_summary, docx_summary)
```
## 📅 Development Timeline
### **Week 1-2: Foundation**
- Project setup and core architecture
- Basic text extraction and metadata tools
- Testing framework and CI/CD
### **Week 3-4: Core Features**
- Table and image extraction
- Document structure analysis
- Format conversion basics
### **Week 5-6: Intelligence**
- Document classification and analysis
- Content summarization
- Health assessment
### **Week 7-8: Advanced Features**
- Document manipulation
- Advanced conversions
- Performance optimization
### **Week 9-10: Polish**
- Comprehensive documentation
- Example creation
- Integration testing
---
## 🎯 Next Steps
1. **Create project repository** with proper structure
2. **Set up development environment** with uv and dependencies
3. **Implement core text extraction** as foundation
4. **Build out tool categories** systematically
5. **Create comprehensive documentation** following PDF Tools model
This companion server will provide the same level of quality and comprehensiveness as MCP PDF Tools, creating a powerful document processing ecosystem for the MCP protocol.

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@ -82,5 +82,7 @@ include = [
[dependency-groups]
dev = [
"pytest>=8.4.1",
"pytest-cov>=6.2.1",
"reportlab>=4.4.3",
]

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@ -1,89 +0,0 @@
#!/usr/bin/env python3
"""
Test script to validate the image extraction fix that avoids verbose base64 output.
"""
import asyncio
import sys
import os
from pathlib import Path
# Add src to path
sys.path.insert(0, 'src')
async def test_image_extraction():
"""Test the updated extract_images function"""
print("🧪 Testing Image Extraction Fix")
print("=" * 50)
try:
# Import the server module
from mcp_pdf_tools.server import CACHE_DIR, format_file_size
import fitz # PyMuPDF
# Test the format_file_size utility function
print("✅ Testing format_file_size utility:")
print(f" 1024 bytes = {format_file_size(1024)}")
print(f" 1048576 bytes = {format_file_size(1048576)}")
print(f" 0 bytes = {format_file_size(0)}")
# Check if test PDF exists
test_pdf = "test_document.pdf"
if not os.path.exists(test_pdf):
print(f"⚠️ Test PDF '{test_pdf}' not found - creating a simple one...")
# Create a simple test PDF with an image
doc = fitz.open()
page = doc.new_page()
page.insert_text((100, 100), "Test PDF with potential images")
doc.save(test_pdf)
doc.close()
print(f"✅ Created test PDF: {test_pdf}")
print(f"\n🔍 Analyzing PDF structure directly...")
doc = fitz.open(test_pdf)
total_images = 0
for page_num in range(len(doc)):
page = doc[page_num]
image_list = page.get_images()
total_images += len(image_list)
print(f" Page {page_num + 1}: {len(image_list)} images found")
doc.close()
if total_images == 0:
print("⚠️ No images found in test PDF - this is expected for a simple text PDF")
print("✅ The fix prevents verbose output by saving to files instead of base64")
print(f"✅ Images would be saved to: {CACHE_DIR}")
print("✅ Response would include file_path, filename, size_bytes, size_human fields")
print("✅ No base64 'data' field that causes verbose output")
else:
print(f"✅ Found {total_images} images - fix would save them to files")
print(f"\n📁 Cache directory: {CACHE_DIR}")
print(f" Exists: {CACHE_DIR.exists()}")
print(f"\n🎯 Summary of Fix:")
print(f" ❌ Before: extract_images returned base64 'data' field (verbose)")
print(f" ✅ After: extract_images saves files and returns paths")
print(f" ❌ Before: pdf_to_markdown included base64 image data (verbose)")
print(f" ✅ After: pdf_to_markdown saves images and references file paths")
print(f" ✅ Added: file_path, filename, size_bytes, size_human fields")
print(f" ✅ Result: Clean, concise output for MCP clients")
return True
except Exception as e:
print(f"❌ Error during testing: {e}")
import traceback
traceback.print_exc()
return False
if __name__ == "__main__":
success = asyncio.run(test_image_extraction())
if success:
print(f"\n🏆 Image extraction fix validated successfully!")
print(f" This resolves the verbose base64 output issue in MCP clients.")
else:
print(f"\n💥 Validation failed - check the errors above.")
sys.exit(0 if success else 1)

112
uv.lock generated
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