Fork of surquest-utils-svg2pptx with opacity, gradient, and image support. Converts SVG to editable PowerPoint presentations.
Project description
suyujay-svg2pptx
Fork of surquest-utils-svg2pptx with additional features.
Additional Features (this fork)
- Opacity Support:
fill-opacityandstroke-opacityattributes - Gradient Support: Linear gradients from
<defs>withurl(#id)references - Image Support: SVG
<image>elements with aspect ratio preservation - Font Mapping: CSS generic font families (
monospace→ Consolas,sans-serif→ Arial,serif→ Times New Roman)
Attribution
Original project by surQuest. Licensed under MIT.
Installation
pip install suyujay-svg2pptx
Features
- Decoupled Architecture: Separate Frontend (Parser), IR Layer, and Backend (Generator).
- Geometric Mapping: Translates SVG shapes (
<rect>,<circle>,<ellipse>,<polygon>) into native PowerPoint shapes. - Smart Text Handling: Maps nested
<text>and<tspan>elements to native text frames with custom styling (font-family, size, weight, color). - Intelligent Connectors: Support for
straight,elbow, andcurverouting with automatic shape anchoring (begin_connect/end_connect). - Arrowhead Support: Recognizes standard SVG markers and maps them to PowerPoint's
arrow,diamond, andstealthline-end types. - Complex Icons: Supports embedding nested
<svg>fragments as high-quality pictures. - Hierarchical Grouping: Reconstructs SVG group structures (
<g>) as native PowerPoint GroupShapes, supporting nested hierarchies. - Styling Preservation: Handles hex colors, CSS color names (e.g.,
orange,blue), stroke widths, corner radii, and translucency (alpha). - Logging Implementation: Uses standard Python
loggingmodule for production-ready monitoring.
SVG Metadata Schema & Requirements
The compiler expects SVG files to conform to specific structural and metadata rules to guide the transformation properly:
Canvas & Styling
- Dimensions: SVG must have viewBox and full widht and height, e.g.
viewBox="0 0 960 540" width="100%" height="100%". - Styling: Use presentation attributes (
fill="#FF5733",stroke="#e0e0e0") ONLY. Do not use inline CSS (style="...") or<style>blocks. - Colors & Transparency: Use 3 or 6-digit hex colors. For opacity, use explicit
fill-opacity="..."orstroke-opacity="..."attributes (0.0 to 1.0) rather than 8-digit hex codes. - Typography: Use standard fonts only (e.g., Arial, Calibri, Segoe UI). Use
<tspan>for rich text formatting.
Structural Rules
- InfoBox (
data-element-type="infoBox"): Wrap logical components in<g id="[unique_id]" data-element-type="infoBox">. - Connectors (
data-element-type="connector"): Must be kept isolated at the root level (never nested inside other<g>groups) as<line>or<polyline>.- Required attributes:
data-start="[source_id]",data-end="[target_id]",data-connector-type="straight|elbow|curve". - Arrowheads: Supported via
marker-startandmarker-endattributes referencing standard marker defs (none,arrow,diamond,stealth).
- Required attributes:
- Icons (
data-element-type="icon"): Isolate inside a group and nest a child<svg>with explicitx,y,width,height, andviewBoxattributes.
Usage
Installation
pip install suyujay-svg2pptx
Simple Conversion (Single Slide)
from surquest.utils.svg2pptx import SVG2Pptx
# Initialize converter
converter = SVG2Pptx()
# Convert SVG file/string to PPTX
converter.convert(
svg_input="input.svg",
output_path="output.pptx"
)
Multi-Slide Conversion
You can generate a multi-slide presentation by providing a list of SVG paths. The slides will be generated in the order provided.
from surquest.utils.svg2pptx import SVG2Pptx
converter = SVG2Pptx()
converter.convert(
svg_input=["slide1.svg", "slide2.svg", "slide3.svg"],
output_path="multi_slide.pptx"
)
Project Structure
.
├── data/ # Sample SVG and JSON IR files
├── prompts/ # System instructions for LLM-based SVG generation
├── scripts/ # Utility scripts (e.g., run.py)
├── src/
│ └── surquest/
│ └── utils/
│ └── svg2pptx/
│ ├── generator/ # PPTX Generator (Backend)
│ ├── models/ # Intermediate Representation (IR) Models
│ ├── parser/ # SVG Parser (Frontend)
│ └── svg2pptx.py # Orchestrator & Main API
├── tests/ # Test suite (unit and integration tests)
├── pyproject.toml # Build and dependency configuration
└── README.md
Advanced Usage
Exporting and Importing Intermediate Representation (JSON)
The compiler allows you to export the Intermediate Representation (IR) to JSON, and recreate presentations directly from the JSON. This is particularly useful for debugging or programmatic manipulation before PPTX generation.
from surquest.utils.svg2pptx import SVG2Pptx
converter = SVG2Pptx()
# 1. Export SVG directly to JSON IR
json_string = converter.to_json("input.svg")
# 2. Convert to PPTX and save the JSON IR simultaneously
converter.convert(
svg_input="input.svg",
output_path="output.pptx",
export_as_json=True # Will also generate output.json
)
# 3. Create a presentation from a saved JSON IR
converter.from_json(
json_input="output.json",
output_path="restored_presentation.pptx"
)
Low level APIs
from surquest.utils.svg2pptx.parser import SVGParser
from surquest.utils.svg2pptx.generator import PPTXBackend
# 1. Parse SVG into Intermediate Representation
parser = SVGParser(svg_source, slide_width=12192000, slide_height=6858000, svg_ns="{http://www.w3.org/2000/svg}")
ir_slide = parser.parse()
# 2. Render IR to PPTX
prs = PPTXBackend([ir_slide]).render()
prs.save("output.pptx")
API Deployment (FastAPI)
This project includes a FastAPI application in the app/ folder that can be deployed to Vercel.
Endpoint: POST /sources/SVG/target/PPTX:convert
Converts raw SVG metadata to a downloadable .pptx file.
Query Parameters:
filename: (Required) The name of the output PPTX file (e.g.,presentation.pptx).
Request Body:
- The request body must be the raw SVG text strings (Content-Type should be
text/plainorimage/svg+xml).
Example Request:
curl -X POST "https://your-app.vercel.app/sources/SVG/target/PPTX:convert?filename=my_slide.pptx" \
-H "Content-Type: text/plain" \
--data-binary "@input.svg"
Local Development
- Install requirements:
pip install -r requirements.txt - Run the server:
uvicorn app.main:app --reload
Vercel Deployment
The project is configured for Vercel via vercel.json. Simply connect your repository to Vercel and it will automatically detect the Python configuration.
Development & Testing
Development Environment (VS Code Dev Container)
This repository includes a VS Code Dev Container configuration to provide a consistent development environment. It uses Python 3.11 on Alpine Linux and comes pre-installed with all necessary C dependencies and Python packages (python-pptx, lxml, pytest, etc.).
- Ensure you have Docker and the Dev Containers extension installed in VS Code.
- Open the project in VS Code and click Reopen in Container when prompted (or use the Command Palette:
Dev Containers: Reopen in Container).
Running Tests
We use pytest for testing. You can run the full test suite with coverage reporting:
pytest tests/
Running the Example
You can use the provided run script to process SVG files in the data/ directory:
python scripts/run.py
License
This project is licensed under the MIT License.
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