docforge-ai 2.0.0

Self-contained AI-powered documentation generator

DocForge - Open Source AI Documentation Generator

DocForge is a powerful, self-contained AI-powered documentation generator that transforms simple project ideas into comprehensive, professional software documentation. Built with CrewAI and OpenAI, it generates enterprise-grade documents including project charters, requirements specifications, architecture documents, and more.

🚀 Features

• PRD-First Workflow: Start with a Product Requirements Document including user stories, validate, then expand
• AI-Powered Generation: Uses advanced AI agents to create professional documentation
• Multiple Document Types: Generate 10+ different types of technical documents
• Self-Contained: No external database dependencies - uses local file storage
• Easy Setup: Simple installation and configuration with .env file
• Professional Quality: Enterprise-grade document templates and formatting
• Document Revision: Revise PRDs with additional specifications using AI
• Contextual Generation: Generate additional documents based on validated PRD content
• Flexible Output: Generate specific document types or complete document sets
• Neat Organization: Documents are stored in organized project directories
• Interactive Setup: Guided initialization with document type selection

📋 Supported Document Types

1. Project Charter - Executive-level project overview with business objectives, scope, and timeline
2. Software Requirements Specification (SRS) - Detailed functional and non-functional requirements with user stories
3. System Architecture - High-level system design with components, security, and scalability
4. Low-Level Design - Detailed technical design with API specifications and database schema
5. Test Specification - Comprehensive testing strategy with test cases and acceptance criteria
6. Deployment Guide - Step-by-step deployment and release procedures
7. Operations Manual - System operations, monitoring, and maintenance procedures
8. Business Case - ROI analysis and business justification for the project
9. Market Requirements - Market analysis and user requirements documentation
10. Vision Brief - Strategic vision and opportunity brief for stakeholders

🛠️ Installation

Prerequisites

• Python 3.8 or higher
• OpenAI API key (Get one here)

Quick Install

Option 1: Install from PyPI (Recommended)

pip install docforge-ai

After installation, use:

python -m docforge.docforge init
python -m docforge.docforge generate "Your project idea"

Option 2: Install from Source

# Clone the repository
git clone https://github.com/docforge-community/docforge-opensource.git
cd docforge-opensource

# Install dependencies
pip install -r requirements.txt

# Initialize DocForge (creates .env file and shows available document types)
python -m docforge.docforge init

Package Installation

# Install from source
pip install .

# Or install in development mode
pip install -e .

⚙️ Configuration

Initial Setup

1. Run initialization to create the .env file:

python -m docforge.docforge init

2. Edit the .env file with your OpenAI API key:

# Required
OPENAI_API_KEY=your_actual_openai_api_key_here

# Optional (defaults shown)
OPENAI_MODEL=gpt-4o-mini
DOCFORGE_GENERATED_DOCS_PATH=generated-docs

3. Get your OpenAI API key from OpenAI Platform

🚀 Quick Start

Interactive Mode (Recommended for first-time users)

python start_docforge.py

Command Line Usage

PRD-First Workflow (Recommended)

The recommended approach is to start with a Product Requirements Document (PRD) that includes user stories, validate it, and then generate additional documents based on the validated PRD.

Step 1: Generate a PRD

# Generate a PRD with user stories
python -m docforge.docforge generate PRD "AI-powered chatbot for customer service"

Step 2: Review and Optionally Revise the PRD

# Review the generated PRD file, then optionally add more specifications
python -m docforge.docforge revise ai-powered-chatbot-for-customer-service -s "Add multi-language support and integration with Slack and Microsoft Teams"

Step 3: Generate Additional Documents Based on Validated PRD

# Generate architecture, testing, and deployment documents based on the PRD
python -m docforge.docforge continue ai-powered-chatbot-for-customer-service ARCH TEST DEPLOY

# Or generate specific documents
python -m docforge.docforge continue ai-powered-chatbot-for-customer-service ARCHITECTURE
python -m docforge.docforge continue ai-powered-chatbot-for-customer-service BUSINESS MARKET

Alternative: Generate Single Documents

# Generate individual documents (without PRD workflow)
python -m docforge.docforge generate SRS "E-commerce platform for handmade crafts"
python -m docforge.docforge generate ARCHITECTURE "Mobile banking application"

Legacy: Generate Complete Documentation Set

# Generate all default documents at once
python -m docforge.docforge generate "E-commerce platform for handmade crafts"
python -m docforge.docforge generate "Mobile task management app" --docs project_charter,srs,architecture

List Available Document Types and Aliases

python -m docforge.docforge list-docs

This command shows all available document types and their quick aliases for single document generation.

🎯 Why Use PRD-First Workflow?

The PRD-first workflow offers several advantages:

1. Validation Before Expansion: Review and validate the core requirements and user stories before generating additional documents
2. Consistency: All subsequent documents are generated based on the same validated PRD, ensuring consistency across the documentation set
3. Iterative Improvement: Easily revise the PRD with additional specifications without regenerating all documents
4. Cost Effective: Generate only what you need - start with PRD, validate, then expand
5. Better Quality: Documents generated from a validated PRD tend to be more accurate and detailed
6. User Story Foundation: PRDs include comprehensive user stories that inform all other documents

Quick Aliases Reference:

• PRD or PR → Software Requirements Specification
• SRS → Software Requirements Specification
• ARCH or ARCHITECTURE or HLD → System Architecture
• LLD or DESIGN → Low-Level Design
• TEST or TESTING → Test Specification
• DEPLOY or DEPLOYMENT → Deployment Guide
• OPS or OPERATIONS → Operations Manual
• BUSINESS → Business Case
• MARKET → Market Requirements
• VISION → Vision Brief
• CHARTER or PROJECT → Project Charter
• CONCEPT → Concept Expansion

Check Project Status

python -m docforge.docforge status my-ecommerce-platform

List All Projects

python -m docforge.docforge list-projects

📁 Project Structure

docforge/
├── docforge.py              # Main CLI interface
├── start_docforge.py        # Interactive startup script
├── docforge/               # Package directory
│   ├── __init__.py
│   └── docforge.py         # Package main module
├── backend/                # Core application logic
│   └── app/
│       ├── core/           # Configuration and settings
│       │   └── simple_config.py
│       ├── models.py       # Data models
│       └── services/       # Business logic services
│           ├── document_agents.py
│           ├── local_storage_service.py
│           └── openai_service.py
├── prompts/                # AI prompt templates
│   ├── charter.md
│   ├── requirements.md
│   ├── architecture.md
│   ├── design.md
│   ├── testing.md
│   ├── deployment.md
│   ├── operations.md
│   ├── business_case.md
│   ├── market_requirements.md
│   └── vision_brief.md
├── storage/                # Local data storage
│   ├── projects/           # Project metadata
│   ├── documents/          # Document metadata
│   └── generated-docs/     # Generated documentation
├── generated-docs/         # User-generated documentation
├── requirements.txt        # Python dependencies
└── .env                    # Configuration file (created by init)

📖 Usage Examples

Example 1: Complete Project Documentation

python -m docforge.docforge generate "AI-powered customer service chatbot" --context "React frontend, Node.js backend, PostgreSQL database"

Example 2: Architecture-Focused Documentation

python -m docforge.docforge generate "Microservices e-commerce platform" --docs architecture,deployment_guide,operations_manual

Example 3: Business-Focused Documentation

python -m docforge.docforge generate "SaaS project management tool" --docs business_case,market_requirements,vision_brief

Example 4: Custom Project Name

python -m docforge.docforge generate "Build a mobile app" --name "MyAwesomeApp" --docs srs,architecture

📂 Document Organization

DocForge organizes your generated documents neatly:

generated-docs/
└── your-project-name/
    ├── README.md                    # Project overview and index
    ├── 01_project_charter.md        # Project charter
    ├── 02_srs.md                    # Software requirements
    ├── 03_architecture.md           # System architecture
    ├── 04_test_specification.md     # Test specification
    └── ...                          # Additional documents

Each project gets its own directory with:

• Sequential numbering for easy navigation
• README.md with project overview and document index
• Clean markdown files ready for use
• Metadata tracking in the storage system

🎯 Document Type Selection

When you run python -m docforge.docforge init, DocForge will show you all available document types:

📋 Available Document Types (10):
 1. Project Charter
     Type: project_charter
     Description: Executive-level project overview with business objectives, scope, and timeline

 2. Software Requirements Specification
     Type: srs
     Description: Detailed functional and non-functional requirements with user stories

 3. System Architecture
     Type: architecture
     Description: High-level system design with components, security, and scalability
...

You can then generate specific documents using the type names:

python -m docforge.docforge generate "My project" --docs project_charter,srs,architecture

🔧 Advanced Configuration

Environment Variables

Variable	Description	Default
OPENAI_API_KEY	OpenAI API key (required)	-
OPENAI_MODEL	OpenAI model to use	gpt-4o-mini
DOCFORGE_GENERATED_DOCS_PATH	Generated docs directory	generated-docs
DOCFORGE_MAX_TOKENS	Max tokens per document	3000
DOCFORGE_DEFAULT_DOCS	Default document types	project_charter,srs,architecture,test_specification

Custom Document Types

You can customize the document generation by modifying the prompt templates in the prompts/ directory.

Storage Configuration

DocForge uses local file storage by default. All data is stored in:

• storage/projects/ - Project metadata (JSON files) - Created automatically when first generating documents
• storage/documents/ - Document metadata (JSON files) - Created automatically when first generating documents
• generated-docs/ - Generated markdown files organized by project - Created during initialization

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Setup

# Clone and setup development environment
git clone https://github.com/docforge-community/docforge-opensource.git
cd docforge-opensource

# Install in development mode
pip install -e .

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

# Run tests
pytest

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

• Documentation: Wiki
• Issues: GitHub Issues
• Discussions: GitHub Discussions

🙏 Acknowledgments

• Built with CrewAI for AI agent orchestration
• Powered by OpenAI for document generation
• Inspired by the need for better software documentation practices

---

Made with ❤️ by the DocForge Community