opendocs 0.1.0

Convert GitHub README files into structured multi-format documentation artifacts.

� OpenDocs

Convert any GitHub README into structured, multi-format documentation — instantly.

What is OpenDocs?

OpenDocs (by IoTEverything) takes a GitHub repository README and automatically generates beautiful, professional documentation in multiple formats:

Output	Format	Status
📄 Technical Report	.docx (Word)	✅
📊 Executive Deck	.pptx (PowerPoint)	✅
📑 PDF Documentation	.pdf	✅
📝 Analysis Report	.md (Markdown)	✅
📐 Mermaid Diagrams	PNG rendering	✅
🧠 Knowledge Graph	Entity extraction	✅
🤖 LLM Summaries	Stakeholder views	✅
🎨 7 Themes	corporate, ocean, sunset, dark, minimal, emerald, royal	✅

Two Modes

1. Basic (Deterministic) — Pure Markdown AST parsing, no LLM required. Fast, free, predictable.
2. LLM (AI-Powered) — Uses OpenAI to extract entities, build knowledge graphs, and generate executive summaries + stakeholder views (CTO, Investor, Developer).

Quick Start

Install from PyPI

pip install opendocs

For LLM features:

pip install opendocs[llm]

Install from source

git clone https://github.com/ioteverythin/OpenDocs.git
cd OpenDocs
pip install -e ".[dev,llm]"

Usage

CLI:

# Generate all formats from a GitHub README
opendocs generate https://github.com/owner/repo

# Generate specific format with a theme
opendocs generate https://github.com/owner/repo --format word --theme ocean

# From a local README file
opendocs generate ./README.md --local

# LLM mode with knowledge graph + stakeholder summaries
opendocs generate ./README.md --local --mode llm --api-key sk-...

# Specify output directory
opendocs generate https://github.com/owner/repo -o ./my-docs

# List available themes
opendocs themes

Python API:

from opendocs.pipeline import Pipeline

pipeline = Pipeline()
pipeline.run(
    "https://github.com/owner/repo",
    theme_name="ocean",
    mode="llm",
    api_key="sk-...",
)

Features

• 7 Built-in Themes — Corporate, Ocean, Sunset, Dark, Minimal, Emerald, Royal
• Mermaid → PNG — Renders mermaid diagrams to images via mermaid.ink API
• Knowledge Graph — Extracts 10+ entity types (projects, technologies, APIs, metrics, etc.)
• Smart Table Sorting — 6 strategies (smart, alpha, numeric, column:N, column:N:desc, none)
• LLM Summaries — Executive summary + CTO / Investor / Developer stakeholder views
• Architecture Diagrams — Auto-generated KG visualization as Mermaid graph

Architecture

GitHub URL / Local .md
        │
        ▼
┌─────────────────┐
│   README Fetch   │  ← httpx + GitHub API
└────────┬────────┘
         ▼
┌─────────────────┐
│  Markdown Parser │  ← mistune 3.x AST
└────────┬────────┘
         ▼
┌─────────────────┐
│  Table Sorting   │  ← 6 strategies
└────────┬────────┘
         ▼
┌─────────────────┐
│  KG Extraction   │  ← Semantic + optional LLM
└────────┬────────┘
         ▼
┌─────────────────┐
│ Diagram Renderer │  ← mermaid.ink API
└────────┬────────┘
         │
    ┌────┼────┬────┬──────┐
    ▼    ▼    ▼    ▼      ▼
  Word  PDF  PPTX  MD  Diagrams

Development

# Install dev dependencies
pip install -e ".[dev,llm]"

# Run tests (114 tests)
pytest

# Lint
ruff check src/

Contributing

Contributions are welcome! Please open issues and PRs on GitHub.

License

MIT License — see LICENSE for details.